A Comparative Study of Metaheuristic Optimization Algorithms for Solving Real-World Engineering Design Problems

Real-world engineering design problems with complex objective functions under some constraints are relatively difficult problems to solve.Such design problems are widely experienced in many engineering fields,such as industry,automotive,construction,machinery,and interdisciplinary research.However,there are established optimization techniques that have shown effectiveness in addressing these types of issues.This research paper gives a comparative study of the implementation of seventeen new metaheuristic methods in order to optimize twelve distinct engineering design issues.The algorithms used in the study are listed as:transient search optimization(TSO),equilibrium optimizer(EO),grey wolf optimizer(GWO),moth-flame optimization(MFO),whale optimization algorithm(WOA),slimemould algorithm(SMA),harris hawks optimization(HHO),chimp optimization algorithm(COA),coot optimization algorithm(COOT),multi-verse optimization(MVO),arithmetic optimization algorithm(AOA),aquila optimizer(AO),sine cosine algorithm(SCA),smell agent optimization(SAO),and seagull optimization algorithm(SOA),pelican optimization algorithm(POA),and coati optimization algorithm(CA).As far as we know,there is no comparative analysis of recent and popular methods against the concrete conditions of real-world engineering problems.Hence,a remarkable research guideline is presented in the study for researchersworking in the fields of engineering and artificial intelligence,especiallywhen applying the optimization methods that have emerged recently.Future research can rely on this work for a literature search on comparisons of metaheuristic optimization methods in real-world problems under similar conditions.

Optimization of magnetic field design for Hall thrusters based on a genetic algorithm

Magnetic field design is essential for the operation of Hall thrusters.This study focuses on utilizing a genetic algorithm to optimize the magnetic field configuration of SPT70.A 2D hybrid PIC-DSMC and channel-wall erosion model are employed to analyze the plume divergence angle and wall erosion rate,while a Farady probe measurement and laser profilometry system are set up to verify the simulation results.The results demonstrate that the genetic algorithm contributes to reducing the divergence angle of the thruster plumes and alleviating the impact of high-energy particles on the discharge channel wall,reducing the erosion by 5.5%and 2.7%,respectively.Further analysis indicates that the change from a divergent magnetic field to a convergent magnetic field,combined with the upstream shift of the ionization region,contributes to the improving the operation of the Hall thruster.

Research on the Application of Intelligent Optimization Algorithm in Mechanical Design

Intelligent optimization algorithm belongs to a kind of emerging technology,show good characteristics,such as high performance,applicability,its algorithm includes many contents,including genetic,particle swarm and artificial neural network algorithm,compared with the traditional optimization way,these algorithms can be applied to a variety of situations,meet the demand of solution,in the mechanical design industry has wide application prospects.This paper analyzes the application of the algorithm in mechanical design and the comparison of the results to verify the significance of the intelligent optimization algorithm in mechanical design.

Quantum algorithm for minimum dominating set problem with circuit design

Using quantum algorithms to solve various problems has attracted widespread attention with the development of quantum computing.Researchers are particularly interested in using the acceleration properties of quantum algorithms to solve NP-complete problems.This paper focuses on the well-known NP-complete problem of finding the minimum dominating set in undirected graphs.To expedite the search process,a quantum algorithm employing Grover’s search is proposed.However,a challenge arises from the unknown number of solutions for the minimum dominating set,rendering direct usage of original Grover’s search impossible.Thus,a swap test method is introduced to ascertain the number of iterations required.The oracle,diffusion operators,and swap test are designed with achievable quantum gates.The query complexity is O(1.414^(n))and the space complexity is O(n).To validate the proposed approach,qiskit software package is employed to simulate the quantum circuit,yielding the anticipated results.

Process design and intensification of multicomponent azeotropes special distillation separation via molecular simulation and system optimization

This work provides an overview of distillation processes,including process design for different distillation processes,selection of entrainers for special distillation processes,system integration and intensification of distillation processes,optimization of process parameters for distillation processes and recent research progress in dynamic control strategies.Firstly,the feasibility of using thermodynamic topological theories such as residual curve,phase equilibrium line and distillation boundary line to analyze different separation regions is discussed,and the rationality of distillation process design is discussed by using its feasibility.Secondly,the application of molecular simulation methods such as molecular dynamics simulation and quantum chemical calculation in the screening of entrainer is discussed for the extractive distillation process.The thermal coupling mechanism of different distillation processes is used to explore the process of different process intensifications.Next,a mixed integer nonlinear optimization strategy for the distillation process based on different algorithms is introduced.Finally,the improvement of dynamic control strategies for different distillation processes in recent years is summarized.This work focuses on the application of process intensification and system optimization in the design of distillation process,and analyzes the challenges,prospects,and development trends of distillation technology in the separation of multicomponent azeotropes.

Vibration Control of the Rail Grinding Vehicle with Abrasive Belt Based on Structural Optimization and Lightweight Design

As a new grinding and maintenance technology,rail belt grinding shows significant advantages in many applications The dynamic characteristics of the rail belt grinding vehicle largely determines its grinding performance and service life.In order to explore the vibration control method of the rail grinding vehicle with abrasive belt,the vibration response changes in structural optimization and lightweight design are respectively analyzed through transient response and random vibration simulations in this paper.Firstly,the transient response simulation analysis of the rail grinding vehicle with abrasive belt is carried out under operating conditions and non-operating conditions.Secondly,the vibration control of the grinding vehicle is implemented by setting vibration isolation elements,optimizing the structure,and increasing damping.Thirdly,in order to further explore the dynamic characteristics of the rail grinding vehicle,the random vibration simulation analysis of the grinding vehicle is carried out under the condition of the horizontal irregularity of the American AAR6 track.Finally,by replacing the Q235 steel frame material with 7075 aluminum alloy and LA43M magnesium alloy,both vibration control and lightweight design can be achieved simultaneously.The results of transient dynamic response analysis show that the acceleration of most positions in the two working conditions exceeds the standard value in GB/T 17426-1998 standard.By optimizing the structure of the grinding vehicle in three ways,the average vibration acceleration of the whole car is reduced by about 55.1%from 15.6 m/s^(2) to 7.0 m/s^(2).The results of random vibration analysis show that the grinding vehicle with Q235 steel frame does not meet the safety conditions of 3σ.By changing frame material,the maximum vibration stress of the vehicle can be reduced from 240.7 MPa to 160.0 MPa and the weight of the grinding vehicle is reduced by about 21.7%from 1500 kg to 1175 kg.The modal analysis results indicate that the vibration control of the grinding vehicle can be realized by optimizing the structure and replacing the materials with lower stiffness under the premise of ensuring the overall strength.The study provides the basis for the development of lightweight,diversified and efficient rail grinding equipment.

Surface wave inversion with unknown number of soil layers based on a hybrid learning procedure of deep learning and genetic algorithm

Surface wave inversion is a key step in the application of surface waves to soil velocity profiling.Currently,a common practice for the process of inversion is that the number of soil layers is assumed to be known before using heuristic search algorithms to compute the shear wave velocity profile or the number of soil layers is considered as an optimization variable.However,an improper selection of the number of layers may lead to an incorrect shear wave velocity profile.In this study,a deep learning and genetic algorithm hybrid learning procedure is proposed to perform the surface wave inversion without the need to assume the number of soil layers.First,a deep neural network is adapted to learn from a large number of synthetic dispersion curves for inferring the layer number.Then,the shear-wave velocity profile is determined by a genetic algorithm with the known layer number.By applying this procedure to both simulated and real-world cases,the results indicate that the proposed method is reliable and efficient for surface wave inversion.

Impact Performance Research of Re-Entrant Octagonal Negative Poisson’s Ratio Honeycomb with Gradient Design

Based on the traditional re-entrant honeycomb,a novel re-entrant octagon honeycomb(ROH)is proposed.The deformation mode of the honeycomb under quasi-static compression is analyzed by numerical simulation,and the results are in good agreement with the experimental ones.The deformation modes,mechanical properties,and energy absorption characteristics of ROH along the impact and perpendicular directions gradient design are investigated under different velocities.The results indicated that the deformation mode of ROH is affected by gradient design along the direction of impact and impact speed.In addition,gradient design along the direction of impact can increase the initial peak stress of ROH and accelerate its densification phase.Gradient design perpendicular to the impact direction can enhance the energy absorption performance of ROH,especially for ROH,with wall thickness increasing from the inside outwards.Compared to ROH with uniform wall thickness at the same relative density,ROH with a gradient design can increase the plateau stress by over half.With the elevation of impact velocity,the plateau stress and specific energy absorption exhibit an upward trend,aligning with the dynamic performance pattern observed in conventional honeycombs.The results can be used as a reference for the design and application of honeycomb and provide a new idea for developing more efficient and reliable energy-absorbing materials.

Design Method for Optimizing the Interactive Interface of Live Broadcasting Platform for the Elderly Users

In the era of network live broadcasting for everyone,the development of live broadcasting platforms is also more intelligent and diversified.However,in the face of a large group of elderly users,the interface interaction design mode used is still mainly based on the interaction mode for young groups,and is not designed for elderly users.Therefore,a design method for optimizing the interaction interface of live broadcasting platform for elderly users was proposed in this study.Firstly,the case study method and Delphi expert survey method were used to determine the design needs of elderly users and the design mode was analysed.Secondly,the orthogonal design principle was used to design a test sample of the interactive interface of live broadcasting platform applicable for the elderly users,and then a user evaluation system was established to calculate the weights of the design elements using hierarchical analysis,and then the predictive relationship between the design mode of the interactive interface of live broadcasting platform and the elderly users was established by Quantitative Theory I.Finally,Genetic Algorithm was applied to generate the optimized design scheme.The results showed that the design method based on the Genetic Algorithm and the combination of Quantitative Theory can scientifically and effectively optimize the design of the interactive interface of the live broadcasting platform for the elderly users,and improve the experience of the elderly users.

Aerodynamic/stealth design of S-duct inlet based on discrete adjoint method

It is a major challenge for the airframe-inlet design of modern combat aircrafts,as the flow and electromagnetic wave propagation in the inlet of stealth aircraft are very complex.In this study,an aerodynamic/stealth optimization design method for an S-duct inlet is proposed.The upwind scheme is introduced to the aerodynamic adjoint equation to resolve the shock wave and flow separation.The multilevel fast multipole algorithm(MLFMA)is utilized for the stealth adjoint equation.A dorsal S-duct inlet of flying wing layout is optimized to improve the aerodynamic and stealth characteristics.Both the aerodynamic and stealth characteristics of the inlet are effectively improved.Finally,the optimization results are analyzed,and it shows that the main contradiction between aerodynamic characteristics and stealth characteristics is the centerline and crosssectional area.The S-duct is smoothed,and the cross-sectional area is increased to improve the aerodynamic characteristics,while it is completely opposite for the stealth design.The radar cross section(RCS)is reduced by phase cancelation for low frequency conditions.The method is suitable for the aerodynamic/stealth design of the aircraft airframe-inlet system.

Optimizing Bucket Elevator Performance through a Blend of Discrete Element Method, Response Surface Methodology, and Firefly Algorithm Approaches

This research introduces a novel approach to enhancing bucket elevator design and operation through the integration of discrete element method(DEM)simulation,design of experiments(DOE),and metaheuristic optimization algorithms.Specifically,the study employs the firefly algorithm(FA),a metaheuristic optimization technique,to optimize bucket elevator parameters for maximizing transport mass and mass flow rate discharge of granular materials under specified working conditions.The experimental methodology involves several key steps:screening experiments to identify significant factors affecting bucket elevator operation,central composite design(CCD)experiments to further explore these factors,and response surface methodology(RSM)to create predictive models for transport mass and mass flow rate discharge.The FA algorithm is then applied to optimize these models,and the results are validated through simulation and empirical experiments.The study validates the optimized parameters through simulation and empirical experiments,comparing results with DEM simulation.The outcomes demonstrate the effectiveness of the FA algorithm in identifying optimal bucket parameters,showcasing less than 10%and 15%deviation for transport mass and mass flow rate discharge,respectively,between predicted and actual values.Overall,this research provides insights into the critical factors influencing bucket elevator operation and offers a systematic methodology for optimizing bucket parameters,contributing to more efficient material handling in various industrial applications.

Analysis and Design of Surgical Instrument Localization Algorithm

With the help of surgical navigation system,doctors can operate on patients more intuitively and accurately.The positioning accuracy and real-time performance of surgical instruments are very important to the whole system.In this paper,we analyze and design the detection algorithm of surgical instrument location mark,and estimate the posture of surgical instrument.In addition,we optimized the pose by remapping.Finally,the algorithm of location mark detection proposed in this paper and the posture analysis data of surgical instruments are verified and analyzed through experiments.The final result shows a high accuracy.

Scheduling Model and Algorithm of Construction Equipment under Milestone Constraint

The scheduling of construction equipment is a means to realize network planning.With the large-scale and low-cost requirements of engineering construction,the cooperation among members of the engineering supply chain has become very important,and effective coordination of project plans at all levels to optimize the resource management and scheduling of a project is helpful to reduce project duration and cost.In this paper,under the milestone constraint conditions,the scheduling problems of multiple construction devices in the same sequence of operation were described and hypothesized mathematically,and the scheduling models of multiple equipment were established.The Palmer algorithm,CDS algorithm and Gupta algorithm were respectively used to solve the optimal scheduling of construction equipment to achieve the optimization of the construction period.The optimization scheduling of a single construction device and multiple construction devices was solved by using sequencing theory under milestone constraint,and these methods can obtain reasonable results,which has important guiding significance for the scheduling of construction equipment.

The Key Path of the Shape Optimization Design of Isotropic Material Pressure Vessels

An optimization design was conducted for the shape of the pressure vessel with a thin-shell shell. During this process, the optimization calculation was performed with the aid of the genetic algorithm toolbox included in Matlab. Firstly, through the parametric modeling function of APDL, models such as arc-shaped, parabolic, elliptical, and those generated by the fitting curve command were successfully constructed. Meanwhile, the relevant settings of material properties were accomplished, and the static analysis was conducted. Secondly, the optimization calculation process was initiated using the genetic algorithm toolbox in Matlab. Eventually, through analysis and judgment, the model generated by the fitting curve command was relatively superior within the category of the best shape.

Application Analysis of Nursing Students'Grades in Course Relevance Based on Association Rule Mining Algorithm Apriori

By analyzing the correlation between courses in students’grades,we can provide a decision-making basis for the revision of courses and syllabi,rationally optimize courses,and further improve teaching effects.With the help of IBM SPSS Modeler data mining software,this paper uses Apriori algorithm for association rule mining to conduct an in-depth analysis of the grades of nursing students in Shandong College of Traditional Chinese Medicine,and to explore the correlation between professional basic courses and professional core courses.Lastly,according to the detailed analysis of the mining results,valuable curriculum information will be found from the actual teaching data.

Flexible Fixture Design for the Top and End Surface Processing of NP2_NP4 Cylinder Heads

This paper focuses on the design of fixtures for NP2 and NP4 cylinder heads on a horizontal machining center of flexible machining automatic lines.It began with an analysis of the diagrams of part processing and working procedure which formed the basis for the design of the processing technology scheme,a selection of suitable machine tools,and the setting of processing parameters.Fixtures tailored to the chosen machine tools were then designed to meet the processing requirements.Additional aspects of the project included the design of part drawings,calculation of working time quota,design of auxiliary guides,support clamping,and hydraulic circuits,all aimed at fulfilling practical production requirements.

Optimal Design of Tapered Roller Bearings Based on Multi⁃Physics Objectives Using Evolutionary Algorithms

Rolling element bearing is the most common machine element in rotating machinery.An extended life is among the foremost imperative standards in the optimal design of rolling element bearings,which confide on the fatigue failure,wear,and thermal conditions of bearings.To fill the gap,in the current work,all three objectives of a tapered roller bearing have been innovatively considered respectively,which are the dynamic capacity,elasto-hydrodynamic lubrication(EHL)minimum film⁃thickness,and maximum bearing temperature.These objective function formulations are presented,associated design variables are identified,and constraints are discussed.To solve complex non⁃linear constrained optimization formulations,a best⁃practice design procedure was investigated using the Artificial Bee Colony(ABC)algorithms.A sensitivity analysis of several geometric design variables was conducted to observe the difference in all three objectives.An excellent enhancement was found in the bearing designs that have been optimized as compared with bearing standards and previously published works.The present study will definitely add to the present experience based design followed in bearing industries to save time and obtain assessment of bearing performance before manufacturing.To verify the improvement,an experimental investigation is worthwhile conducting.

Grey-theory based algorithm for impact assessment of green design

Life cycle assessment (LCA) is an important content of green design;the major phase of LCA is impact assessment. After classifying the impact factors, with grey-system theory, the evaluating grey-groups and their whitening weighing functions are defined;the grey-cluster analysis of each classified impact is performed;based on analyzing results, the calculating method of classified impact index is given. By range of action, the impact classes are grouped to three groups - global impact, regional impact, and local impact;the calculating methods of grouped and overall impact index are presented. Finally, an application example of comparative choice of a category of products - three materials, steel, aluminum and engineering plastics is given.

Lightweight Design of Commercial Vehicle Cab Based on Fatigue Durability

To better improve the lightweight and fatigue durability performance of the tractor cab,a multi-objective lightweight design of the cab was carried out in this study.First,the finite element model of the cab with counterweight loading was established and then confirmed by the physical testing,and use the inertial reliefmethod to obtain stress distribution under unit load.The cab-frame rigid-flexible couplingmulti-body dynamicsmodelwas built by Adams/car software.Taking the cab airbag mount displacement and acceleration signals acquired on the proving ground as the desired signals and obtaining the fatigue analysis load spectrum through Femfat-Lab virtual iteration.The fatigue simulation analysis is performed in nCode based on the Miner linear fatigue cumulative damage theory.Then,with themass and fatigue damage values as the optimization objectives,the bending-torsional stiffness and first-order bending-torsional mode as constraints,the thickness variables are screed based on the sensitivity analysis.The experimental design was carried out using the Optimal Latin hypercube method,and the multi-objective optimal design of the cab was carried out using theKriging approximationmodel fitting and particle swarmalgorithm.The weight of the optimized cab is reduced by 7.8%on the basis of meeting the fatigue durability performance.Finally,a seven-axis road simulation test rig was designed to verify its fatigue durability.The results show the optimized cab can consider both lightweight and durability.

An Improved Elite Slime Mould Algorithm for Engineering Design

The Swarm intelligence algorithm is a very prevalent field in which some scholars have made outstanding achievements.As a representative,Slime mould algorithm(SMA)is widely used because of its superior initial performance.Therefore,this paper focuses on the improvement of the SMA and the mitigation of its stagnation problems.For this aim,the structure of SMA is adjusted to develop the efficiency of the original method.As a stochastic optimizer,SMA mainly stimulates the behavior of slime mold in nature.For the harmony of the exploration and exploitation of SMA,the paper proposed an enhanced algorithm of SMA called ECSMA,in which two mechanisms are embedded into the structure:elite strategy,and chaotic stochastic strategy.The details of the original SMA and the two introduced strategies are given in this paper.Then,the advantages of the improved SMA through mechanism comparison,balance-diversity analysis,and contrasts with other counterparts are validated.The experimental results demonstrate that both mechanisms have a significant enhancing effect on SMA.Also,SMA is applied to four structural design issues of the welded beam design problem,PV design problem,I-beam design problem,and cantilever beam design problem with excellent results.