The feasibility and kinetics of lead recovery from the slag of traditional lead melting furnace using chloride leaching were investigated.The effects of operating parameters such as leaching time,NaCl concentration,Fe...The feasibility and kinetics of lead recovery from the slag of traditional lead melting furnace using chloride leaching were investigated.The effects of operating parameters such as leaching time,NaCl concentration,FeCl3concentration,liquid/solid ratio,stirring rate,temperature,and particle size on recovery of lead were studied and the optimization was done through the response surface methodology(RSM)based on central composite design(CCD)model.The optimum conditions were achieved as follows:leaching time60min,80°C,stirring rate800r/min,NaCl concentration200g/L,FeCl3concentration80g/L,liquid/solid ratio16,and particle size less than106μm.More than96%of lead was effectively recovered in optimum condition.Based on analysis of variance,the reaction temperature,liquid/solid ratio,and NaCl concentration were determined as the most effective parameters on leaching process,respectively.Kinetics study revealed that chloride leaching of galena is a first-order reaction and the diffusion through solid reaction product and chemical reaction control the mechanism.The activation energy of chloride leaching of galena was determined using Arrhenius model as27.9kJ/mol.展开更多
A new metal-organic framework(MOF) with the chemical formula of [Ni_(2) F_2(4,4'-Bipy)_(2)(H_(2) O)_(2)](VO_(3))_(2)·8 H_(2) O was introduced to adsorb Pb(Ⅱ) with the highest capacity.The sorbent was charact...A new metal-organic framework(MOF) with the chemical formula of [Ni_(2) F_2(4,4'-Bipy)_(2)(H_(2) O)_(2)](VO_(3))_(2)·8 H_(2) O was introduced to adsorb Pb(Ⅱ) with the highest capacity.The sorbent was characterized by thermogravimetric analysis(TGA),infrared spectroscopy(FT-IR),field-emission scanning electron microscopy(FESEM),energy-dispersive Xray(EDX),and elemental analysis.The optimum conditions were obtained by a face-centered central composite design(FCCD) as follows:adsorbent dosage(m)=1.2 mg, initial concentration of Pb(Ⅱ)(C)=390 mg·L^(-1),and pH=5.According to the Langmuir model(R~2=0.9999),the maximum monolayer uptake capacity of lead(Ⅱ) is 2400.7 mg·g^(-1),which is the highe st observed amount for lead(Ⅱ) adsorption.Neither of the old adsorbents for lead(Ⅱ)has the uptake capacity over 2000 mg·g^(-1).The model of pseudo-second-order describes well the process kinetics.The adsorption process of lead(Ⅱ) is independent of temperature changes.This compound can adsorb lead(Ⅱ) from tap water.In addition to introducing a new MOF with the highest uptake capacity for removal of Pb(Ⅱ) that is the outright novelty of this study,the concurrent modeling of both the removal percent(R) and the uptake capacity(q) is another important advantage.Because it achieves the more economical and favorable optimum conditions in comparison with the single optimization of each response.展开更多
Natural adsorbents such as banana pseudostem can play a vital role in the removal of heavy metal elements from wastewater. Major water resources and chemical industries have been encountering difficulties in re- movin...Natural adsorbents such as banana pseudostem can play a vital role in the removal of heavy metal elements from wastewater. Major water resources and chemical industries have been encountering difficulties in re- moving heavy metal elements using available conventional methods. This work demonstrates the potential to treat various effluents utilizing natural materials. A characterization of banana pseudostem powder was performed using environmental scanning electron microscopy (ESEM) and Fourier-transform infrared (FTIR) spectroscopy before and after the adsorption of lead(Ⅱ). Experiments were carried out using a batch process for the removal of lead(Ⅱ) from an aqueous solution. The effects of the adsorption kinetics were studied by altering various parameters such as initial pH, adsorbent dosage, initial lead ion concentration, and contact time. The results show that the point of zero charge (PZC) for the banana pseudostem powder was achieved at a pH of 5.5. The experimental data were analyzed using isotherm and kinetic models. The adsorption of lead(Ⅱ) onto banana pseudostem powder was fitted using the Langmuir adsorption isotherm. The adsorp- tion capacity was found to be 34.21 mg·g-1, and the pseudo second-order kinetic model showed the best fit. The optimum conditions were found using response surface methodology. The maximum removal was found to be 89%.展开更多
Optimization plays an effective role in various disciplines of science and engineering.Optimization problems should either be optimized using the appropriate method(i.e.,minimization or maximization).Optimization algo...Optimization plays an effective role in various disciplines of science and engineering.Optimization problems should either be optimized using the appropriate method(i.e.,minimization or maximization).Optimization algorithms are one of the efficient and effective methods in providing quasioptimal solutions for these type of problems.In this study,a new algorithm called the Mutated Leader Algorithm(MLA)is presented.The main idea in the proposed MLA is to update the members of the algorithm population in the search space based on the guidance of a mutated leader.In addition to information about the best member of the population,themutated leader also contains information about the worst member of the population,as well as other normal members of the population.The proposed MLA is mathematically modeled for implementation on optimization problems.A standard set consisting of twenty-three objective functions of different types of unimodal,fixed-dimensional multimodal,and high-dimensional multimodal is used to evaluate the ability of the proposed algorithm in optimization.Also,the results obtained from theMLA are compared with eight well-known algorithms.The results of optimization of objective functions show that the proposed MLA has a high ability to solve various optimization problems.Also,the analysis and comparison of the performance of the proposed MLA against the eight compared algorithms indicates the superiority of the proposed algorithm and ability to provide more suitable quasi-optimal solutions.展开更多
High-efficiency recovery of Zn and Pb from silicon-rich zinc leaching residues is realized in a rotary kiln.Characterizations by means of XRD,SEM,EDS and ICP reveal that the leaching residue contains 12.4 wt.%SiO_(2),...High-efficiency recovery of Zn and Pb from silicon-rich zinc leaching residues is realized in a rotary kiln.Characterizations by means of XRD,SEM,EDS and ICP reveal that the leaching residue contains 12.4 wt.%SiO_(2),16.1 wt.%Zn,and 7.4 wt.%Pb.Thermodynamic analysis shows that metallic vapor of Zn and Pb can be easily generated from the zinc leaching residue at 1150-1250°C inside the rotary kiln.Viscosities and melting points of 13 slag compositions were analyzed and three slag compositions(47wt.%SiO_(2)-23wt.%CaO-30wt.%FeO,40wt.%SiO_(2)-28wt.%CaO-32wt.%FeO,and 40wt.%SiO_(2)-30wt.%CaO-30wt.%FeO)possessed the desirable physical properties,with the melting point and viscosity in the range of 1150-1280°C and 0.2-0.5 Pa·s,respectively.The industrial tests show that adopting the optimized slag composition can contribute to very high recovery rates of Zn and Pb(97.3%for Zn and 94.5%for Pb),corresponding to slags with very low average contents of Zn and Pb(0.51 wt.%Zn and 0.45 wt.%Pb).The National-Standard leaching tests of the water-quenched slags result in 1.82 mg/L Zn,~0.01 mg/L Cu,0.0004 mg/L As,~0.01 mg/L Cd,0.08 mg/L Pb,and~0.02 mg/L Hg in the leachate,verifying the detoxification of the zinc leaching residue at the same time.展开更多
An efficient chlorination roasting process for recovering zinc(Zn)and lead(Pb)from copper smelting slag was proposed.Thermodynamic models were established,illustrating that Zn and Pb in copper smelting slag can be eff...An efficient chlorination roasting process for recovering zinc(Zn)and lead(Pb)from copper smelting slag was proposed.Thermodynamic models were established,illustrating that Zn and Pb in copper smelting slag can be efficiently recycled during the chlorination roasting process.By decreasing the partial pressure of the gaseous products,chlorination was promoted.The Box−Behnken design was applied to assessing the interactive effects of the process variables and optimizing the chlorination roasting process.CaCl_(2) dosage and roasting temperature and time were used as variables,and metal recovery efficiencies were used as responses.When the roasting temperature was 1172℃ with a CaCl_(2) addition amount of 30 wt.%and a roasting time of 100 min,the predicted optimal recovery efficiencies of Zn and Pb were 87.85%and 99.26%,respectively,and the results were validated by experiments under the same conditions.The residual Zn-and Pb-containing phases in the roasting slags were ZnFe_(2)O_(4),Zn_(2)SiO_(4),and PbS.展开更多
Lean manufacturing has been used for the last few decades as a process and performance improvement tool.Initially known as Toyota production system(TPS),lean is now used in almost all service and manufacturing sectors...Lean manufacturing has been used for the last few decades as a process and performance improvement tool.Initially known as Toyota production system(TPS),lean is now used in almost all service and manufacturing sectors to deliver favorable results such as decreased operational cost,increased customer satisfaction,decreased cycle time,and enhanced profits.During the coronavirus disease(COVID 19)pandemic,the manufacturing sector struggled immensely and could not function well even after lockdown was eased in many countries.Many companies found out there are not ready to conform with new regulations made by authorities in many countries.This paper proposes the use of simulation and multi response optimization in addition to other typical lean tools in order to arrive at optimum performance at the end of each project through an established optimization framework.The framework is used in a real case study performed at an aluminum extrusion factory.Lean manufacturing helps organizations to operate with smaller number of resources.It standardizes all processes so that most of the jobs can be done by most of the workers,but this is not enough to create a healthy,sanitized work place.Our framework utilizes the strengths of lean tools and adds pandemic readiness factor to them to ensure improvement in performance and health pandemic readiness.Implementation of the framework in the case company resulted in 50%reduction in labor,$730000 in expected annual cost savings,reduction in inventory levels,improved employee morale and the achievement of pandemic ready status.展开更多
An optimal design configuration of leading edge extensions (LEXs) is presented based on the standard genetic algorithms (GAs). Aircraft longitudinal dynamic response of the system with and without LEX is analyzed ...An optimal design configuration of leading edge extensions (LEXs) is presented based on the standard genetic algorithms (GAs). Aircraft longitudinal dynamic response of the system with and without LEX is analyzed by solving the state equation of aircraft longitudinal motion. Aerodynamic force, moments, and longitudinal stability derivatives are estimated by three-dimensional low-order panel method. A novel aircraft model with LEX is optimized and its lift curve slope is increased by 13%-17% for Ma=0. 4-0. 9 and 12% for Ma=1. 5. Numerical results show that because the frequency and damping ratio in a short period are improved, the aircraft rapidly responds to a specified deflection control input in the battle area when LEX is installed. Finally, compared the results from the panel method with those from the Cy-20 aircraft flight test data,aerodynamic characteristics are verified.展开更多
The science of complexity studies the behavior and properties of complex systems in nature and human society. Particular interest has been put on their certain simple common properties. Symmetry is one of such propert...The science of complexity studies the behavior and properties of complex systems in nature and human society. Particular interest has been put on their certain simple common properties. Symmetry is one of such properties. Symmetric phenomena can be found in many complex systems. The purpose of this paper is to reveal the internal reason of the symmetry. Using some physical systems and geometric objects, the paper shows that many symmetries are caused by optimization under certain criteria. It has also been revealed that an evolutional process may lead to symmetry.展开更多
In classification problems,datasets often contain a large amount of features,but not all of them are relevant for accurate classification.In fact,irrelevant features may even hinder classification accuracy.Feature sel...In classification problems,datasets often contain a large amount of features,but not all of them are relevant for accurate classification.In fact,irrelevant features may even hinder classification accuracy.Feature selection aims to alleviate this issue by minimizing the number of features in the subset while simultaneously minimizing the classification error rate.Single-objective optimization approaches employ an evaluation function designed as an aggregate function with a parameter,but the results obtained depend on the value of the parameter.To eliminate this parameter’s influence,the problem can be reformulated as a multi-objective optimization problem.The Whale Optimization Algorithm(WOA)is widely used in optimization problems because of its simplicity and easy implementation.In this paper,we propose a multi-strategy assisted multi-objective WOA(MSMOWOA)to address feature selection.To enhance the algorithm’s search ability,we integrate multiple strategies such as Levy flight,Grey Wolf Optimizer,and adaptive mutation into it.Additionally,we utilize an external repository to store non-dominant solution sets and grid technology is used to maintain diversity.Results on fourteen University of California Irvine(UCI)datasets demonstrate that our proposed method effectively removes redundant features and improves classification performance.The source code can be accessed from the website:https://github.com/zc0315/MSMOWOA.展开更多
This study presents the elaboration of a simple and cheap electrode made by carbon paste introduced into a cavity of electrode body, and used for the lead traces determination in tap water. A potentiostatic pre-electr...This study presents the elaboration of a simple and cheap electrode made by carbon paste introduced into a cavity of electrode body, and used for the lead traces determination in tap water. A potentiostatic pre-electrolysis at constant voltage enables the reduction of the lead (Pb2+) and the accumulation of the metallic lead at and into the carbon paste;the reoxidation of the Pb (Linear sweep voltammetry) leads to the anodic striping peak. The effect of the main operating parameters on the shape of the peak and the magnitude of the current was examined and their optimal values were determined. Then calibration was achieved and the method was successfully applied (using all the optimized parameters) to the determination of lead in water, with a detection limit of 0.138 μg·L-1. Compared to other methods (ICP-AES for example), the proposed method offers a satisfactory detection limit of the Pb2+ (0.138 μg·L-1) because of the important specific area of the carbon paste electrode, for a significantly lower cost. Besides, there is no observed loss in the electrode answer in terms of peak current, which means that there is no any irreversible steps nor deactivation of the electrode, even after ten successive measurements;only reduction of the lead followed by the deposit oxidation was observed at the electrode.展开更多
Cloud computing provides a diverse and adaptable resource pool over the internet,allowing users to tap into various resources as needed.It has been seen as a robust solution to relevant challenges.A significant delay ...Cloud computing provides a diverse and adaptable resource pool over the internet,allowing users to tap into various resources as needed.It has been seen as a robust solution to relevant challenges.A significant delay can hamper the performance of IoT-enabled cloud platforms.However,efficient task scheduling can lower the cloud infrastructure’s energy consumption,thus maximizing the service provider’s revenue by decreasing user job processing times.The proposed Modified Chimp-Whale Optimization Algorithm called Modified Chimp-Whale Optimization Algorithm(MCWOA),combines elements of the Chimp Optimization Algorithm(COA)and the Whale Optimization Algorithm(WOA).To enhance MCWOA’s identification precision,the Sobol sequence is used in the population initialization phase,ensuring an even distribution of the population across the solution space.Moreover,the traditional MCWOA’s local search capabilities are augmented by incorporating the whale optimization algorithm’s bubble-net hunting and random search mechanisms into MCWOA’s position-updating process.This study demonstrates the effectiveness of the proposed approach using a two-story rigid frame and a simply supported beam model.Simulated outcomes reveal that the new method outperforms the original MCWOA,especially in multi-damage detection scenarios.MCWOA excels in avoiding false positives and enhancing computational speed,making it an optimal choice for structural damage detection.The efficiency of the proposed MCWOA is assessed against metrics such as energy usage,computational expense,task duration,and delay.The simulated data indicates that the new MCWOA outpaces other methods across all metrics.The study also references the Whale Optimization Algorithm(WOA),Chimp Algorithm(CA),Ant Lion Optimizer(ALO),Genetic Algorithm(GA)and Grey Wolf Optimizer(GWO).展开更多
Magnesium(Mg),being the lightest structural metal,holds immense potential for widespread applications in various fields.The development of high-performance and cost-effective Mg alloys is crucial to further advancing ...Magnesium(Mg),being the lightest structural metal,holds immense potential for widespread applications in various fields.The development of high-performance and cost-effective Mg alloys is crucial to further advancing their commercial utilization.With the rapid advancement of machine learning(ML)technology in recent years,the“data-driven''approach for alloy design has provided new perspectives and opportunities for enhancing the performance of Mg alloys.This paper introduces a novel regression-based Bayesian optimization active learning model(RBOALM)for the development of high-performance Mg-Mn-based wrought alloys.RBOALM employs active learning to automatically explore optimal alloy compositions and process parameters within predefined ranges,facilitating the discovery of superior alloy combinations.This model further integrates pre-established regression models as surrogate functions in Bayesian optimization,significantly enhancing the precision of the design process.Leveraging RBOALM,several new high-performance alloys have been successfully designed and prepared.Notably,after mechanical property testing of the designed alloys,the Mg-2.1Zn-2.0Mn-0.5Sn-0.1Ca alloy demonstrates exceptional mechanical properties,including an ultimate tensile strength of 406 MPa,a yield strength of 287 MPa,and a 23%fracture elongation.Furthermore,the Mg-2.7Mn-0.5Al-0.1Ca alloy exhibits an ultimate tensile strength of 211 MPa,coupled with a remarkable 41%fracture elongation.展开更多
Marine umbilical is one of the key equipment for subsea oil and gas exploitation,which is usually integrated by a great number of different functional components with multi-layers.The layout of these components direct...Marine umbilical is one of the key equipment for subsea oil and gas exploitation,which is usually integrated by a great number of different functional components with multi-layers.The layout of these components directly affects manufacturing,operation and storage performances of the umbilical.For the multi-layer cross-sectional layout design of the umbilical,a quantifiable multi-objective optimization model is established according to the operation and storage requirements.Considering the manufacturing factors,the multi-layering strategy based on contact point identification is introduced for a great number of functional components.Then,the GA-GLM global optimization algorithm is proposed combining the genetic algorithm and the generalized multiplier method,and the selection operator of the genetic algorithm is improved based on the steepest descent method.Genetic algorithm is used to find the optimal solution in the global space,which can converge from any initial layout to the feasible layout solution.The feasible layout solution is taken as the initial value of the generalized multiplier method for fast and accurate solution.Finally,taking umbilicals with a great number of components as examples,the results show that the cross-sectional performance of the umbilical obtained by optimization algorithm is better and the solution efficiency is higher.Meanwhile,the multi-layering strategy is effective and feasible.The design method proposed in this paper can quickly obtain the optimal multi-layer cross-sectional layout,which replaces the manual design,and provides useful reference and guidance for the umbilical industry.展开更多
The current methods used to industrially produce sinomenine hydrochloride involve several issues,including high solvent toxicity,long process flow,and low atomic utilization efficiency,and the greenness scores of the ...The current methods used to industrially produce sinomenine hydrochloride involve several issues,including high solvent toxicity,long process flow,and low atomic utilization efficiency,and the greenness scores of the processes are below 65 points.To solve these problems,a new process using anisole as the extractant was proposed.Anisole exhibits high selectivity for sinomenine and can be connected to the subsequent water-washing steps.After alkalization of the medicinal material,heating extraction,water washing,and acidification crystallization were carried out.The process was modeled and optimized.The design space was constructed.The recommended operating ranges for the critical process parameters were 3.0–4.0 h for alkalization time,60.0–80.0℃ for extraction temperature,2.0–3.0(volume ratio)for washing solution amount,and 2.0–2.4 mol·L^(-1) for hydrochloric acid concentration.The new process shows good robustness because different batches of medicinal materials did not greatly impact crystal purity or sinomenine transfer rate.The sinomenine transfer rate was about 20%higher than that of industrial processes.The greenness score increased to 90 points since the novel process proposed in this research solves the problems of long process flow,high solvent toxicity,and poor atomic economy,better aligning with the concept of green chemistry.展开更多
This research presents a novel nature-inspired metaheuristic algorithm called Frilled Lizard Optimization(FLO),which emulates the unique hunting behavior of frilled lizards in their natural habitat.FLO draws its inspi...This research presents a novel nature-inspired metaheuristic algorithm called Frilled Lizard Optimization(FLO),which emulates the unique hunting behavior of frilled lizards in their natural habitat.FLO draws its inspiration from the sit-and-wait hunting strategy of these lizards.The algorithm’s core principles are meticulously detailed and mathematically structured into two distinct phases:(i)an exploration phase,which mimics the lizard’s sudden attack on its prey,and(ii)an exploitation phase,which simulates the lizard’s retreat to the treetops after feeding.To assess FLO’s efficacy in addressing optimization problems,its performance is rigorously tested on fifty-two standard benchmark functions.These functions include unimodal,high-dimensional multimodal,and fixed-dimensional multimodal functions,as well as the challenging CEC 2017 test suite.FLO’s performance is benchmarked against twelve established metaheuristic algorithms,providing a comprehensive comparative analysis.The simulation results demonstrate that FLO excels in both exploration and exploitation,effectively balancing these two critical aspects throughout the search process.This balanced approach enables FLO to outperform several competing algorithms in numerous test cases.Additionally,FLO is applied to twenty-two constrained optimization problems from the CEC 2011 test suite and four complex engineering design problems,further validating its robustness and versatility in solving real-world optimization challenges.Overall,the study highlights FLO’s superior performance and its potential as a powerful tool for tackling a wide range of optimization problems.展开更多
Unmanned Aero Vehicles (UAV) has become a useful entity for quite a good number of industries and facilities. It is an agile, cost effective and reliable solution for communication, defense, security, delivery, survei...Unmanned Aero Vehicles (UAV) has become a useful entity for quite a good number of industries and facilities. It is an agile, cost effective and reliable solution for communication, defense, security, delivery, surveillance and surveying etc. However, their reliability is dependent on the resilient and stabilizes performance based on control systems embedded behind the body. Therefore, the UAV is majorly dependent upon controller design and the requirement of particular performance parameters. Nevertheless, in modern technologies there is always a room for improvement. In the similar manner a UAV lateral control system was implemented and researched in this study, which has been optimized using Proportional, Integral and Derivative (PID) controller, phase lead compensator and signal constraint controller. The significance of this study is the optimization of the existing UAV controller plant for improving lateral performance and stability. With this UAV community will benefit from designing robust controls using the optimized method utilized in this paper and moreover this will provide sophisticated control to operate in unpredictable environments. It is observed that results obtained for optimized lateral control dynamics using phase lead compensator (PLC) are efficacious than the simple PID feedback gains. However, for optimizing unwanted signals of lateral velocity, yaw rate, and yaw angle modes, PLC were integrated with PID to achieve dynamical stability.展开更多
Catenary optics enables metasurfaces with higher efficiency and wider bandwidth,and is highly anticipated in the imaging system,super-resolution lithography,and broadband absorbers.However,the periodic boundary approx...Catenary optics enables metasurfaces with higher efficiency and wider bandwidth,and is highly anticipated in the imaging system,super-resolution lithography,and broadband absorbers.However,the periodic boundary approximation without considering aperiodic electromagnetic crosstalk poses challenges for catenary optical devices to reach their performance limits.Here,perfect control of both local geometric and propagation phases is realized through field-driven optimization,in which the field distribution is calculated under real boundary conditions.Different from other optimization methods requiring a mass of iterations,the proposed design method requires less than ten iterations to get the efficiency close to the optimal value.Based on the library of shape-optimized catenary structures,centimeter-scale devices can be designed in ten seconds,with the performance improved by ~15%.Furthermore,this method has the ability to extend catenary-like continuous structures to arbitrary polarization,including both linear and elliptical polarizations,which is difficult to achieve with traditional design methods.It provides a way for the development of catenary optics and serves as a potent tool for constructing high-performance optical devices.展开更多
In this article, a novel scalarization technique, called the improved objective-constraint approach, is introduced to find efficient solutions of a given multiobjective programming problem. The presented scalarized pr...In this article, a novel scalarization technique, called the improved objective-constraint approach, is introduced to find efficient solutions of a given multiobjective programming problem. The presented scalarized problem extends the objective-constraint problem. It is demonstrated that how adding variables to the scalarized problem, can lead to find conditions for (weakly, properly) Pareto optimal solutions. Applying the obtained necessary and sufficient conditions, two algorithms for generating the Pareto front approximation of bi-objective and three-objective programming problems are designed. These algorithms are easy to implement and can achieve an even approximation of (weakly, properly) Pareto optimal solutions. These algorithms can be generalized for optimization problems with more than three criterion functions, too. The effectiveness and capability of the algorithms are demonstrated in test problems.展开更多
The structural optimization of wireless sensor networks is a critical issue because it impacts energy consumption and hence the network’s lifetime.Many studies have been conducted for homogeneous networks,but few hav...The structural optimization of wireless sensor networks is a critical issue because it impacts energy consumption and hence the network’s lifetime.Many studies have been conducted for homogeneous networks,but few have been performed for heterogeneouswireless sensor networks.This paper utilizes Rao algorithms to optimize the structure of heterogeneous wireless sensor networks according to node locations and their initial energies.The proposed algorithms lack algorithm-specific parameters and metaphorical connotations.The proposed algorithms examine the search space based on the relations of the population with the best,worst,and randomly assigned solutions.The proposed algorithms can be evaluated using any routing protocol,however,we have chosen the well-known routing protocols in the literature:Low Energy Adaptive Clustering Hierarchy(LEACH),Power-Efficient Gathering in Sensor Information Systems(PEAGSIS),Partitioned-based Energy-efficient LEACH(PE-LEACH),and the Power-Efficient Gathering in Sensor Information Systems Neural Network(PEAGSIS-NN)recent routing protocol.We compare our optimized method with the Jaya,the Particle Swarm Optimization-based Energy Efficient Clustering(PSO-EEC)protocol,and the hybrid Harmony Search Algorithm and PSO(HSA-PSO)algorithms.The efficiencies of our proposed algorithms are evaluated by conducting experiments in terms of the network lifetime(first dead node,half dead nodes,and last dead node),energy consumption,packets to cluster head,and packets to the base station.The experimental results were compared with those obtained using the Jaya optimization algorithm.The proposed algorithms exhibited the best performance.The proposed approach successfully prolongs the network lifetime by 71% for the PEAGSIS protocol,51% for the LEACH protocol,10% for the PE-LEACH protocol,and 73% for the PEGSIS-NN protocol;Moreover,it enhances other criteria such as energy conservation,fitness convergence,packets to cluster head,and packets to the base station.展开更多
文摘The feasibility and kinetics of lead recovery from the slag of traditional lead melting furnace using chloride leaching were investigated.The effects of operating parameters such as leaching time,NaCl concentration,FeCl3concentration,liquid/solid ratio,stirring rate,temperature,and particle size on recovery of lead were studied and the optimization was done through the response surface methodology(RSM)based on central composite design(CCD)model.The optimum conditions were achieved as follows:leaching time60min,80°C,stirring rate800r/min,NaCl concentration200g/L,FeCl3concentration80g/L,liquid/solid ratio16,and particle size less than106μm.More than96%of lead was effectively recovered in optimum condition.Based on analysis of variance,the reaction temperature,liquid/solid ratio,and NaCl concentration were determined as the most effective parameters on leaching process,respectively.Kinetics study revealed that chloride leaching of galena is a first-order reaction and the diffusion through solid reaction product and chemical reaction control the mechanism.The activation energy of chloride leaching of galena was determined using Arrhenius model as27.9kJ/mol.
文摘A new metal-organic framework(MOF) with the chemical formula of [Ni_(2) F_2(4,4'-Bipy)_(2)(H_(2) O)_(2)](VO_(3))_(2)·8 H_(2) O was introduced to adsorb Pb(Ⅱ) with the highest capacity.The sorbent was characterized by thermogravimetric analysis(TGA),infrared spectroscopy(FT-IR),field-emission scanning electron microscopy(FESEM),energy-dispersive Xray(EDX),and elemental analysis.The optimum conditions were obtained by a face-centered central composite design(FCCD) as follows:adsorbent dosage(m)=1.2 mg, initial concentration of Pb(Ⅱ)(C)=390 mg·L^(-1),and pH=5.According to the Langmuir model(R~2=0.9999),the maximum monolayer uptake capacity of lead(Ⅱ) is 2400.7 mg·g^(-1),which is the highe st observed amount for lead(Ⅱ) adsorption.Neither of the old adsorbents for lead(Ⅱ)has the uptake capacity over 2000 mg·g^(-1).The model of pseudo-second-order describes well the process kinetics.The adsorption process of lead(Ⅱ) is independent of temperature changes.This compound can adsorb lead(Ⅱ) from tap water.In addition to introducing a new MOF with the highest uptake capacity for removal of Pb(Ⅱ) that is the outright novelty of this study,the concurrent modeling of both the removal percent(R) and the uptake capacity(q) is another important advantage.Because it achieves the more economical and favorable optimum conditions in comparison with the single optimization of each response.
基金印度Siddaganga Institute of Technology化学工程和生物技术系的支持~~
文摘Natural adsorbents such as banana pseudostem can play a vital role in the removal of heavy metal elements from wastewater. Major water resources and chemical industries have been encountering difficulties in re- moving heavy metal elements using available conventional methods. This work demonstrates the potential to treat various effluents utilizing natural materials. A characterization of banana pseudostem powder was performed using environmental scanning electron microscopy (ESEM) and Fourier-transform infrared (FTIR) spectroscopy before and after the adsorption of lead(Ⅱ). Experiments were carried out using a batch process for the removal of lead(Ⅱ) from an aqueous solution. The effects of the adsorption kinetics were studied by altering various parameters such as initial pH, adsorbent dosage, initial lead ion concentration, and contact time. The results show that the point of zero charge (PZC) for the banana pseudostem powder was achieved at a pH of 5.5. The experimental data were analyzed using isotherm and kinetic models. The adsorption of lead(Ⅱ) onto banana pseudostem powder was fitted using the Langmuir adsorption isotherm. The adsorp- tion capacity was found to be 34.21 mg·g-1, and the pseudo second-order kinetic model showed the best fit. The optimum conditions were found using response surface methodology. The maximum removal was found to be 89%.
基金PT(corresponding author)was supported by the Excellence project PrF UHK No.2202/2020-2022 and Long-term development plan of UHK for year 2021,University of Hradec Králové,Czech Republic,https://www.uhk.cz/en/faculty-of-science/about-faculty/offic ial-board/internal-regulations-and-governing-acts/governing-acts/deans-decision/2020#grant-competi tion-of-fos-uhk-excellence-for-2020.
文摘Optimization plays an effective role in various disciplines of science and engineering.Optimization problems should either be optimized using the appropriate method(i.e.,minimization or maximization).Optimization algorithms are one of the efficient and effective methods in providing quasioptimal solutions for these type of problems.In this study,a new algorithm called the Mutated Leader Algorithm(MLA)is presented.The main idea in the proposed MLA is to update the members of the algorithm population in the search space based on the guidance of a mutated leader.In addition to information about the best member of the population,themutated leader also contains information about the worst member of the population,as well as other normal members of the population.The proposed MLA is mathematically modeled for implementation on optimization problems.A standard set consisting of twenty-three objective functions of different types of unimodal,fixed-dimensional multimodal,and high-dimensional multimodal is used to evaluate the ability of the proposed algorithm in optimization.Also,the results obtained from theMLA are compared with eight well-known algorithms.The results of optimization of objective functions show that the proposed MLA has a high ability to solve various optimization problems.Also,the analysis and comparison of the performance of the proposed MLA against the eight compared algorithms indicates the superiority of the proposed algorithm and ability to provide more suitable quasi-optimal solutions.
基金the funding support from the National Natural Science Foundation of China (Nos. 51804221, 51874101)the National Key R&D Program of China (No. 2019YFF0217102)the China Postdoctoral Science Foundation (Nos. 2018M642906, 2019T120684)
文摘High-efficiency recovery of Zn and Pb from silicon-rich zinc leaching residues is realized in a rotary kiln.Characterizations by means of XRD,SEM,EDS and ICP reveal that the leaching residue contains 12.4 wt.%SiO_(2),16.1 wt.%Zn,and 7.4 wt.%Pb.Thermodynamic analysis shows that metallic vapor of Zn and Pb can be easily generated from the zinc leaching residue at 1150-1250°C inside the rotary kiln.Viscosities and melting points of 13 slag compositions were analyzed and three slag compositions(47wt.%SiO_(2)-23wt.%CaO-30wt.%FeO,40wt.%SiO_(2)-28wt.%CaO-32wt.%FeO,and 40wt.%SiO_(2)-30wt.%CaO-30wt.%FeO)possessed the desirable physical properties,with the melting point and viscosity in the range of 1150-1280°C and 0.2-0.5 Pa·s,respectively.The industrial tests show that adopting the optimized slag composition can contribute to very high recovery rates of Zn and Pb(97.3%for Zn and 94.5%for Pb),corresponding to slags with very low average contents of Zn and Pb(0.51 wt.%Zn and 0.45 wt.%Pb).The National-Standard leaching tests of the water-quenched slags result in 1.82 mg/L Zn,~0.01 mg/L Cu,0.0004 mg/L As,~0.01 mg/L Cd,0.08 mg/L Pb,and~0.02 mg/L Hg in the leachate,verifying the detoxification of the zinc leaching residue at the same time.
基金The authors are grateful for the financial supports from the National Natural Science Foundation of China(Nos.51620105013,51904351)Innovation-Driven Project of Central South University,China(No.2020CX028)+1 种基金Natural Science Fund for Distinguished Young Scholar of Hunan Province,China(No.2019JJ20031)the National Key R&D Program of China(No.2019YFC1907400)。
文摘An efficient chlorination roasting process for recovering zinc(Zn)and lead(Pb)from copper smelting slag was proposed.Thermodynamic models were established,illustrating that Zn and Pb in copper smelting slag can be efficiently recycled during the chlorination roasting process.By decreasing the partial pressure of the gaseous products,chlorination was promoted.The Box−Behnken design was applied to assessing the interactive effects of the process variables and optimizing the chlorination roasting process.CaCl_(2) dosage and roasting temperature and time were used as variables,and metal recovery efficiencies were used as responses.When the roasting temperature was 1172℃ with a CaCl_(2) addition amount of 30 wt.%and a roasting time of 100 min,the predicted optimal recovery efficiencies of Zn and Pb were 87.85%and 99.26%,respectively,and the results were validated by experiments under the same conditions.The residual Zn-and Pb-containing phases in the roasting slags were ZnFe_(2)O_(4),Zn_(2)SiO_(4),and PbS.
文摘Lean manufacturing has been used for the last few decades as a process and performance improvement tool.Initially known as Toyota production system(TPS),lean is now used in almost all service and manufacturing sectors to deliver favorable results such as decreased operational cost,increased customer satisfaction,decreased cycle time,and enhanced profits.During the coronavirus disease(COVID 19)pandemic,the manufacturing sector struggled immensely and could not function well even after lockdown was eased in many countries.Many companies found out there are not ready to conform with new regulations made by authorities in many countries.This paper proposes the use of simulation and multi response optimization in addition to other typical lean tools in order to arrive at optimum performance at the end of each project through an established optimization framework.The framework is used in a real case study performed at an aluminum extrusion factory.Lean manufacturing helps organizations to operate with smaller number of resources.It standardizes all processes so that most of the jobs can be done by most of the workers,but this is not enough to create a healthy,sanitized work place.Our framework utilizes the strengths of lean tools and adds pandemic readiness factor to them to ensure improvement in performance and health pandemic readiness.Implementation of the framework in the case company resulted in 50%reduction in labor,$730000 in expected annual cost savings,reduction in inventory levels,improved employee morale and the achievement of pandemic ready status.
文摘An optimal design configuration of leading edge extensions (LEXs) is presented based on the standard genetic algorithms (GAs). Aircraft longitudinal dynamic response of the system with and without LEX is analyzed by solving the state equation of aircraft longitudinal motion. Aerodynamic force, moments, and longitudinal stability derivatives are estimated by three-dimensional low-order panel method. A novel aircraft model with LEX is optimized and its lift curve slope is increased by 13%-17% for Ma=0. 4-0. 9 and 12% for Ma=1. 5. Numerical results show that because the frequency and damping ratio in a short period are improved, the aircraft rapidly responds to a specified deflection control input in the battle area when LEX is installed. Finally, compared the results from the panel method with those from the Cy-20 aircraft flight test data,aerodynamic characteristics are verified.
基金The work done by the second and third authors are partly supported by the National Natural Saence Foundation of China (No. 60343001,60274010).
文摘The science of complexity studies the behavior and properties of complex systems in nature and human society. Particular interest has been put on their certain simple common properties. Symmetry is one of such properties. Symmetric phenomena can be found in many complex systems. The purpose of this paper is to reveal the internal reason of the symmetry. Using some physical systems and geometric objects, the paper shows that many symmetries are caused by optimization under certain criteria. It has also been revealed that an evolutional process may lead to symmetry.
基金supported in part by the Natural Science Youth Foundation of Hebei Province under Grant F2019403207in part by the PhD Research Startup Foundation of Hebei GEO University under Grant BQ2019055+3 种基金in part by the Open Research Project of the Hubei Key Laboratory of Intelligent Geo-Information Processing under Grant KLIGIP-2021A06in part by the Fundamental Research Funds for the Universities in Hebei Province under Grant QN202220in part by the Science and Technology Research Project for Universities of Hebei under Grant ZD2020344in part by the Guangxi Natural Science Fund General Project under Grant 2021GXNSFAA075029.
文摘In classification problems,datasets often contain a large amount of features,but not all of them are relevant for accurate classification.In fact,irrelevant features may even hinder classification accuracy.Feature selection aims to alleviate this issue by minimizing the number of features in the subset while simultaneously minimizing the classification error rate.Single-objective optimization approaches employ an evaluation function designed as an aggregate function with a parameter,but the results obtained depend on the value of the parameter.To eliminate this parameter’s influence,the problem can be reformulated as a multi-objective optimization problem.The Whale Optimization Algorithm(WOA)is widely used in optimization problems because of its simplicity and easy implementation.In this paper,we propose a multi-strategy assisted multi-objective WOA(MSMOWOA)to address feature selection.To enhance the algorithm’s search ability,we integrate multiple strategies such as Levy flight,Grey Wolf Optimizer,and adaptive mutation into it.Additionally,we utilize an external repository to store non-dominant solution sets and grid technology is used to maintain diversity.Results on fourteen University of California Irvine(UCI)datasets demonstrate that our proposed method effectively removes redundant features and improves classification performance.The source code can be accessed from the website:https://github.com/zc0315/MSMOWOA.
文摘This study presents the elaboration of a simple and cheap electrode made by carbon paste introduced into a cavity of electrode body, and used for the lead traces determination in tap water. A potentiostatic pre-electrolysis at constant voltage enables the reduction of the lead (Pb2+) and the accumulation of the metallic lead at and into the carbon paste;the reoxidation of the Pb (Linear sweep voltammetry) leads to the anodic striping peak. The effect of the main operating parameters on the shape of the peak and the magnitude of the current was examined and their optimal values were determined. Then calibration was achieved and the method was successfully applied (using all the optimized parameters) to the determination of lead in water, with a detection limit of 0.138 μg·L-1. Compared to other methods (ICP-AES for example), the proposed method offers a satisfactory detection limit of the Pb2+ (0.138 μg·L-1) because of the important specific area of the carbon paste electrode, for a significantly lower cost. Besides, there is no observed loss in the electrode answer in terms of peak current, which means that there is no any irreversible steps nor deactivation of the electrode, even after ten successive measurements;only reduction of the lead followed by the deposit oxidation was observed at the electrode.
文摘Cloud computing provides a diverse and adaptable resource pool over the internet,allowing users to tap into various resources as needed.It has been seen as a robust solution to relevant challenges.A significant delay can hamper the performance of IoT-enabled cloud platforms.However,efficient task scheduling can lower the cloud infrastructure’s energy consumption,thus maximizing the service provider’s revenue by decreasing user job processing times.The proposed Modified Chimp-Whale Optimization Algorithm called Modified Chimp-Whale Optimization Algorithm(MCWOA),combines elements of the Chimp Optimization Algorithm(COA)and the Whale Optimization Algorithm(WOA).To enhance MCWOA’s identification precision,the Sobol sequence is used in the population initialization phase,ensuring an even distribution of the population across the solution space.Moreover,the traditional MCWOA’s local search capabilities are augmented by incorporating the whale optimization algorithm’s bubble-net hunting and random search mechanisms into MCWOA’s position-updating process.This study demonstrates the effectiveness of the proposed approach using a two-story rigid frame and a simply supported beam model.Simulated outcomes reveal that the new method outperforms the original MCWOA,especially in multi-damage detection scenarios.MCWOA excels in avoiding false positives and enhancing computational speed,making it an optimal choice for structural damage detection.The efficiency of the proposed MCWOA is assessed against metrics such as energy usage,computational expense,task duration,and delay.The simulated data indicates that the new MCWOA outpaces other methods across all metrics.The study also references the Whale Optimization Algorithm(WOA),Chimp Algorithm(CA),Ant Lion Optimizer(ALO),Genetic Algorithm(GA)and Grey Wolf Optimizer(GWO).
基金supported by the National Natural the Science Foundation of China(51971042,51901028)the Chongqing Academician Special Fund(cstc2020yszxjcyj X0001)+1 种基金the China Scholarship Council(CSC)Norwegian University of Science and Technology(NTNU)for their financial and technical support。
文摘Magnesium(Mg),being the lightest structural metal,holds immense potential for widespread applications in various fields.The development of high-performance and cost-effective Mg alloys is crucial to further advancing their commercial utilization.With the rapid advancement of machine learning(ML)technology in recent years,the“data-driven''approach for alloy design has provided new perspectives and opportunities for enhancing the performance of Mg alloys.This paper introduces a novel regression-based Bayesian optimization active learning model(RBOALM)for the development of high-performance Mg-Mn-based wrought alloys.RBOALM employs active learning to automatically explore optimal alloy compositions and process parameters within predefined ranges,facilitating the discovery of superior alloy combinations.This model further integrates pre-established regression models as surrogate functions in Bayesian optimization,significantly enhancing the precision of the design process.Leveraging RBOALM,several new high-performance alloys have been successfully designed and prepared.Notably,after mechanical property testing of the designed alloys,the Mg-2.1Zn-2.0Mn-0.5Sn-0.1Ca alloy demonstrates exceptional mechanical properties,including an ultimate tensile strength of 406 MPa,a yield strength of 287 MPa,and a 23%fracture elongation.Furthermore,the Mg-2.7Mn-0.5Al-0.1Ca alloy exhibits an ultimate tensile strength of 211 MPa,coupled with a remarkable 41%fracture elongation.
基金financially supported by the National Natural Science Foundation of China(Grant Nos.52001088,52271269,U1906233)the Natural Science Foundation of Heilongjiang Province(Grant No.LH2021E050)+2 种基金the State Key Laboratory of Ocean Engineering(Grant No.GKZD010084)Liaoning Province’s Xing Liao Talents Program(Grant No.XLYC2002108)Dalian City Supports Innovation and Entrepreneurship Projects for High-Level Talents(Grant No.2021RD16)。
文摘Marine umbilical is one of the key equipment for subsea oil and gas exploitation,which is usually integrated by a great number of different functional components with multi-layers.The layout of these components directly affects manufacturing,operation and storage performances of the umbilical.For the multi-layer cross-sectional layout design of the umbilical,a quantifiable multi-objective optimization model is established according to the operation and storage requirements.Considering the manufacturing factors,the multi-layering strategy based on contact point identification is introduced for a great number of functional components.Then,the GA-GLM global optimization algorithm is proposed combining the genetic algorithm and the generalized multiplier method,and the selection operator of the genetic algorithm is improved based on the steepest descent method.Genetic algorithm is used to find the optimal solution in the global space,which can converge from any initial layout to the feasible layout solution.The feasible layout solution is taken as the initial value of the generalized multiplier method for fast and accurate solution.Finally,taking umbilicals with a great number of components as examples,the results show that the cross-sectional performance of the umbilical obtained by optimization algorithm is better and the solution efficiency is higher.Meanwhile,the multi-layering strategy is effective and feasible.The design method proposed in this paper can quickly obtain the optimal multi-layer cross-sectional layout,which replaces the manual design,and provides useful reference and guidance for the umbilical industry.
基金supported by the Innovation Team and Talents Cultivation Program of the National Administration of Traditional Chinese Medicine(ZYYCXTD-D-202002)the Fundamental Research Funds for the Central Universities(226-2022-00226).
文摘The current methods used to industrially produce sinomenine hydrochloride involve several issues,including high solvent toxicity,long process flow,and low atomic utilization efficiency,and the greenness scores of the processes are below 65 points.To solve these problems,a new process using anisole as the extractant was proposed.Anisole exhibits high selectivity for sinomenine and can be connected to the subsequent water-washing steps.After alkalization of the medicinal material,heating extraction,water washing,and acidification crystallization were carried out.The process was modeled and optimized.The design space was constructed.The recommended operating ranges for the critical process parameters were 3.0–4.0 h for alkalization time,60.0–80.0℃ for extraction temperature,2.0–3.0(volume ratio)for washing solution amount,and 2.0–2.4 mol·L^(-1) for hydrochloric acid concentration.The new process shows good robustness because different batches of medicinal materials did not greatly impact crystal purity or sinomenine transfer rate.The sinomenine transfer rate was about 20%higher than that of industrial processes.The greenness score increased to 90 points since the novel process proposed in this research solves the problems of long process flow,high solvent toxicity,and poor atomic economy,better aligning with the concept of green chemistry.
文摘This research presents a novel nature-inspired metaheuristic algorithm called Frilled Lizard Optimization(FLO),which emulates the unique hunting behavior of frilled lizards in their natural habitat.FLO draws its inspiration from the sit-and-wait hunting strategy of these lizards.The algorithm’s core principles are meticulously detailed and mathematically structured into two distinct phases:(i)an exploration phase,which mimics the lizard’s sudden attack on its prey,and(ii)an exploitation phase,which simulates the lizard’s retreat to the treetops after feeding.To assess FLO’s efficacy in addressing optimization problems,its performance is rigorously tested on fifty-two standard benchmark functions.These functions include unimodal,high-dimensional multimodal,and fixed-dimensional multimodal functions,as well as the challenging CEC 2017 test suite.FLO’s performance is benchmarked against twelve established metaheuristic algorithms,providing a comprehensive comparative analysis.The simulation results demonstrate that FLO excels in both exploration and exploitation,effectively balancing these two critical aspects throughout the search process.This balanced approach enables FLO to outperform several competing algorithms in numerous test cases.Additionally,FLO is applied to twenty-two constrained optimization problems from the CEC 2011 test suite and four complex engineering design problems,further validating its robustness and versatility in solving real-world optimization challenges.Overall,the study highlights FLO’s superior performance and its potential as a powerful tool for tackling a wide range of optimization problems.
文摘Unmanned Aero Vehicles (UAV) has become a useful entity for quite a good number of industries and facilities. It is an agile, cost effective and reliable solution for communication, defense, security, delivery, surveillance and surveying etc. However, their reliability is dependent on the resilient and stabilizes performance based on control systems embedded behind the body. Therefore, the UAV is majorly dependent upon controller design and the requirement of particular performance parameters. Nevertheless, in modern technologies there is always a room for improvement. In the similar manner a UAV lateral control system was implemented and researched in this study, which has been optimized using Proportional, Integral and Derivative (PID) controller, phase lead compensator and signal constraint controller. The significance of this study is the optimization of the existing UAV controller plant for improving lateral performance and stability. With this UAV community will benefit from designing robust controls using the optimized method utilized in this paper and moreover this will provide sophisticated control to operate in unpredictable environments. It is observed that results obtained for optimized lateral control dynamics using phase lead compensator (PLC) are efficacious than the simple PID feedback gains. However, for optimizing unwanted signals of lateral velocity, yaw rate, and yaw angle modes, PLC were integrated with PID to achieve dynamical stability.
基金financial supports from the National Natural Science Foundation of China (No.62175242,U20A20217,61975210,and 62305345)China Postdoctoral Science Foundation (2021T140670)。
文摘Catenary optics enables metasurfaces with higher efficiency and wider bandwidth,and is highly anticipated in the imaging system,super-resolution lithography,and broadband absorbers.However,the periodic boundary approximation without considering aperiodic electromagnetic crosstalk poses challenges for catenary optical devices to reach their performance limits.Here,perfect control of both local geometric and propagation phases is realized through field-driven optimization,in which the field distribution is calculated under real boundary conditions.Different from other optimization methods requiring a mass of iterations,the proposed design method requires less than ten iterations to get the efficiency close to the optimal value.Based on the library of shape-optimized catenary structures,centimeter-scale devices can be designed in ten seconds,with the performance improved by ~15%.Furthermore,this method has the ability to extend catenary-like continuous structures to arbitrary polarization,including both linear and elliptical polarizations,which is difficult to achieve with traditional design methods.It provides a way for the development of catenary optics and serves as a potent tool for constructing high-performance optical devices.
文摘In this article, a novel scalarization technique, called the improved objective-constraint approach, is introduced to find efficient solutions of a given multiobjective programming problem. The presented scalarized problem extends the objective-constraint problem. It is demonstrated that how adding variables to the scalarized problem, can lead to find conditions for (weakly, properly) Pareto optimal solutions. Applying the obtained necessary and sufficient conditions, two algorithms for generating the Pareto front approximation of bi-objective and three-objective programming problems are designed. These algorithms are easy to implement and can achieve an even approximation of (weakly, properly) Pareto optimal solutions. These algorithms can be generalized for optimization problems with more than three criterion functions, too. The effectiveness and capability of the algorithms are demonstrated in test problems.
文摘The structural optimization of wireless sensor networks is a critical issue because it impacts energy consumption and hence the network’s lifetime.Many studies have been conducted for homogeneous networks,but few have been performed for heterogeneouswireless sensor networks.This paper utilizes Rao algorithms to optimize the structure of heterogeneous wireless sensor networks according to node locations and their initial energies.The proposed algorithms lack algorithm-specific parameters and metaphorical connotations.The proposed algorithms examine the search space based on the relations of the population with the best,worst,and randomly assigned solutions.The proposed algorithms can be evaluated using any routing protocol,however,we have chosen the well-known routing protocols in the literature:Low Energy Adaptive Clustering Hierarchy(LEACH),Power-Efficient Gathering in Sensor Information Systems(PEAGSIS),Partitioned-based Energy-efficient LEACH(PE-LEACH),and the Power-Efficient Gathering in Sensor Information Systems Neural Network(PEAGSIS-NN)recent routing protocol.We compare our optimized method with the Jaya,the Particle Swarm Optimization-based Energy Efficient Clustering(PSO-EEC)protocol,and the hybrid Harmony Search Algorithm and PSO(HSA-PSO)algorithms.The efficiencies of our proposed algorithms are evaluated by conducting experiments in terms of the network lifetime(first dead node,half dead nodes,and last dead node),energy consumption,packets to cluster head,and packets to the base station.The experimental results were compared with those obtained using the Jaya optimization algorithm.The proposed algorithms exhibited the best performance.The proposed approach successfully prolongs the network lifetime by 71% for the PEAGSIS protocol,51% for the LEACH protocol,10% for the PE-LEACH protocol,and 73% for the PEGSIS-NN protocol;Moreover,it enhances other criteria such as energy conservation,fitness convergence,packets to cluster head,and packets to the base station.