Application of Stork Optimization Algorithm for Solving Sustainable Lot Size Optimization

The efficiency of businesses is often hindered by the challenges encountered in traditional Supply Chain Manage-ment(SCM),which is characterized by elevated risks due to inadequate accountability and transparency.To address these challenges and improve operations in green manufacturing,optimization algorithms play a crucial role in supporting decision-making processes.In this study,we propose a solution to the green lot size optimization issue by leveraging bio-inspired algorithms,notably the Stork Optimization Algorithm(SOA).The SOA draws inspiration from the hunting and winter migration strategies employed by storks in nature.The theoretical framework of SOA is elaborated and mathematically modeled through two distinct phases:exploration,based on migration simulation,and exploitation,based on hunting strategy simulation.To tackle the green lot size optimization issue,our methodology involved gathering real-world data,which was then transformed into a simplified function with multiple constraints aimed at optimizing total costs and minimizing CO_(2) emissions.This function served as input for the SOA model.Subsequently,the SOA model was applied to identify the optimal lot size that strikes a balance between cost-effectiveness and sustainability.Through extensive experimentation,we compared the performance of SOA with twelve established metaheuristic algorithms,consistently demonstrating that SOA outperformed the others.This study’s contribution lies in providing an effective solution to the sustainable lot-size optimization dilemma,thereby reducing environmental impact and enhancing supply chain efficiency.The simulation findings underscore that SOA consistently achieves superior outcomes compared to existing optimization methodologies,making it a promising approach for green manufacturing and sustainable supply chain management.

Back Frame Section Size Optimization of Large Aperture Telescope

The back frame structure of a large radio telescope is an important component supporting the reflecting surface,which is directly related to the surface precision.Its optimal design is of key significance for ensuring the surface precision and reducing structural weight.Two methods are constructed to optimize the cross-section size of the telescope back frame in this paper,the criterion method and the first-order optimization method.The criterion method is based on the Lagrangian multiplier method and Kuhn-Tucker condition.This method first establishes the mathematical model by taking the inner and outer radiuses of the back frame beams as the design variables,the structural weight as the constraint condition,and the structural compliance as the objective function,then derives the optimization criterion.The first-order optimization method takes the inner and outer radiuses of the beams as the design variables,the back frame RMS as the objective function,and the structural weight as the constraint condition.Comparison of RMS,structural stress uniformity and optimization efficiency shows that both algorithms can effectively reduce structural deformation and improve RMS,but the criterion method has relatively better result than the first-order method.

Dielectric size optimization for high power density in large-scale triboelectric nanogenerators

Triboelectric nanogenerators(TENGs)have emerged as a promising technology to harvest electrical energy from natural motions such as human movement,wind,and water flow.Although TENGs show significant potential in small-scale applications,developing large-scale TENGs capable of generating high power remains a significant challenge.Several factors that can affect the performance of large-scale TENGs are being investigated to overcome this challenge,including the size and configuration of dielectric materials.This study optimizes dielectrics regarding surface area,thickness,and multicell configuration to improve harvested electrical power density in large-scale TENGs.In the studies,glass fiber was used as the positive dielectric,and multipurpose white silicone was used as the negative dielectric because of their high tribo-potential,durability,and easy accessibility.In the size optimization phase,dielectric thicknesses and surface areas that provide the maximum power density were determined.Subsequently,horizontal and vertical multicell configurations were examined to efficiently integrate size-optimized dielectrics.The results reveal that large-scale TENGs with vertical multicell configurations can achieve high and usable energy density for electronics.The findings provide valuable insight into the development of large-scale TENGs with advanced power generation capabilities.

Geopolymer-based modification of blasting sealing materials and optimization of blasting block size in coal seams of open pit mines

This research proposes the utilization of a geopolymer-based blasting sealing material to improve the profitability of coal sales and reduce the rate of coal fragmentation during blasting in open pit mines.The study first focused on optimizing the strength of the sealant material and reducing curing time.This was achieved by regulating the slag doping and sodium silicate solution modulus.The findings demonstrated that increasing slag content and improving the material resulted in an early rise in strength while increasing the modulus of the sodium silicate solution extended the curing time.The slag doping level was fixed at 80 g,and the sodium silicate solution modulus was set at 1.5.To achieve a strength of 3.12 MPa,the water/gel ratio was set at 0.5.The initial setting time was determined to be 33 min,meeting the required field test duration.Secondly,the strength requirements for field implementation were assessed by simulating the action time and force destruction process of the sealing material during blasting using ANSYS/LS-DYNA software.The results indicated that the modified material meets these requirements.Finally,the Shengli Open Pit Coal Mine served as the site for the field test.It was observed that the hole-sealing material’s hydration reaction created a laminated and flocculated gel inside it.This enhanced the density of the modified material.Additionally,the pregelatinized starch,functioning as an organic binder,filled the gaps between the gels,enhancing the cohesion and bonding coefficient of the material.Upon analyzing the post-blasting shooting effect diagram using the Split-Desktop software,it was determined that the utilization of the modified blast hole plugging material resulted in a decrease in the rate of coal fragmentation from 33.2%to 21.1%.This reduction exhibited a minimal error of 1.63%when compared to the field measurement,thereby providing further confirmation of the exceptional plugging capabilities of the modified material.This study significantly contributes to establishing a solid theoretical basis for enhancing the blasting efficiency of open pit mines and,in turn,enhancing their economic advantages.

An Improved JSO and Its Application in Spreader Optimization of Large Span Corridor Bridge

In this paper,given the shortcomings of jellyfish search algorithmwith low search ability in the early stage and easy to fall into local optimal solution,this paper introduces adaptive weight function and elite strategy,improving the global search scope in the early stage and the ability to refine the local development in the later stage.In the numerical study,the benchmark problem of dimensional optimization with a 10-bar truss structure and simultaneous dimensional shape optimization with a 15-bar truss structure is adopted,and the corresponding penalty method is used for constraint treatment.The test results show that the improved jellyfish search algorithm can provide better truss sections as well as weights.Because when the steel main truss of the large-span covered bridge is lifted,the site is limited and the large lifting equipment cannot enter the site,and the original structure does not meet the problem of stress concentration and large deformation of the bolt group,so the spreader is used to lift,and the improved jellyfish search algorithm is introduced into the design optimization of the spreader.The results show that the improved jellyfish algorithm can efficiently and accurately find out the optimal shape and weight of the spreader,and throughMidas Civil simulation,the spreader used canmeet the requirements of weight and safety.

THE SATELLITE STRUCTURE TOPOLOGY OPTIMIZATION BASED ON HOMOGENIZATION METHOD AND ITS SIZE SENSITIVITY ANALYSIS

With the development of satellite structure technology, more and more design parameters will affect its structural performance. It is desirable to obtain an optimal structure design with a minimum weight, including optimal configuration and sizes. The present paper aims to describe an optimization analysis for a satellite structure, including topology optimization and size optimization. Based on the homogenization method, the topology optimization is carried out for the main supporting frame of service module under given constraints and load conditions, and then the sensitivity analysis is made of 15 structural size parameters of the whole satellite and the optimal sizes are obtained. The numerical result shows that the present optimization design method is very effective.

INTEGRATION SHAPE AND SIZING OPTIMIZATION OF COMPOSITE WING STRUCTURE BASED ON RESPONSE SURFACE METHOD

An effective optimization method for the shape/sizing design of composite wing structures is presented with satisfying weight-cutting results. After decoupling, a kind of two-layer cycled optimization strategy suitable for these integrated shape/sizing optimization is obtained. The uniform design method is used to provide sample points, and approximation models for shape design variables. And the results of sizing optimization are construct- ed with the quadratic response surface method （QRSM）. The complex method based on QRSM is used to opti- mize the shape design variables and the criteria method is adopted to optimize the sizing design variables. Compared with the conventional method, the proposed algorithm is more effective and feasible for solving complex composite optimization problems and has good efficiency in weight cutting.

Light-Weight Design Method for Force-Performance-Structure of Complex Structural Part Based Co-operative Optimization

A light?weight design method of integrated structural topology and size co?optimization for the force?performance?structure of complex structural parts is presented in this paper. Firstly, the supporting function of a complex structural part is built to map the force transmission, where the force exerted areas and constraints are considered as connecting structure and the structural configuration, to determine the part performance as well as the force routines. Then the connecting structure design model, aiming to optimize the static and dynamic performances on connection configuration, is developed, and the optimum design of the characteristic parameters is carried out by means of the collaborative optimization method, namely, the integrated structural topology optimization and size optimization. In this design model, the objective is to maximize the connecting stiffness. Based on the relationship between the force and the structural configuration of a part, the optimal force transmission routine that can meet the performance requirements is obtained using the structural topology optimization technology. Accordingly, the light?weight design of conceptual configuration for complex parts under multi?objective and multi?condition can be realized. Finally, based on the proposed collaborative optimization design method, the optimal performance and optimal structure of the complex parts with light weight are realized, and the reasonable structural unit configuration and size charac?teristic parameters are obtained. A bed structure of gantry?type machining center is designed by using the proposed light?weight structure design method in this paper, as an illustrative example. The bed after the design optimization is lighter 8% than original one, and the rail deformation is reduced by 5%. Moreover, the lightweight design of the bed is achieved with enhanced performance to show the effectiveness of the proposed method.

Impacts of sample size for stomach content analysis on the estimation of ecosystem indices

This study used Ecopath model of the Jiaozhou Bay as an example to evaluate the effect of stomach sample size of three fish species on the projection of this model. The derived ecosystem indices were classified into three categories:(1) direct indices, like the trophic level of species, influenced by stomach sample size directly;(2)indirect indices, like ecology efficiency(EE) of invertebrates, influenced by the multiple prey-predator relationships;and(3) systemic indices, like total system throughout(TST), describing the status of the whole ecosystem. The influences of different stomach sample sizes on these indices were evaluated. The results suggest that systemic indices of the ecosystem model were robust to stomach sample sizes, whereas specific indices related to species were indicated to be with low accuracy and precision when stomach samples were insufficient.The indices became more uncertain when the stomach sample sizes varied for more species. This study enhances the understanding of how the quality of diet composition data influences ecosystem modeling outputs. The results can also guide the design of stomach content analysis for developing ecosystem models.

AHP-Based Optimal Selection of Garment Sizes for Online Shopping

Garment online shopping has been accepted by more and more consumers in recent years. In online shopping, a buyer only chooses the garment size judged by his own experience without trying-on, so the selected garment may not be the fittest one for the buyer due to the variety of body's figures. Thus, we propose a method of optimal selection of garment sizes for online shopping based on Analytic Hierarchy Process (AHP). The hierarchical structure model for optimal selection of garment sizes is structured and the fittest garment for a buyer is found by calculating the matching degrees between individual's measurements and the corresponding key-part values of ready-to-wear clothing sizes. In order to demonstrate its feasibility, we provide an example of selecting the fittest sizes of men's bottom. The result shows that the proposed method is useful in online clothing sales application.

A Simple Method of Calculating the Optimal Step Size in 4DVAR Technique

In four—dimensional variational data assimilation (4DVAR) technology, how to calculate the optimal step size is always a very important and indeed difficult task. It is directly related to the computational efficiency. In this research, a new method is proposed to calculate the optimal step size more effectively. Both nonlinear one—dimensional advection equation and two—dimensional inertial wave equation are used to test and compare the influence of different methods of the optimal step size calculations on the iteration steps, as well as the simulation results of 4DVAR processes. It is in evidence that the different methods have different influences. The calculating method is very important to determining whether the iteration is convergent or not and whether the convergence rate is large or small. If the calculating method of optimal step size is properly determined as demonstrated in this paper, then it can greatly enlarge the convergence rate and further greatly decrease the iteration steps. This research is meaningful since it not only makes an important improvement on 4DVAR theory, but also has useful practical application in improving the computational efficiency and saving the computational time. Key words 4DVAR - Optimal step size - Iterative convergence rate This work was supported by the National Natural Science Foundation under grants: 49735180 and 49675259, the “973 Project? CHERES(G 1998040907), the Project of Natural Science Foundation of Jiangsu Province(BK99020), and the Project Sponsored by the Scientific Research Foundation for the Returned Overseas Chinese Scholars.

An NLMS algorithm with optimized preparatory step-size parameters for SQUID-based MCG data processing

We present a new least-mean-square algorithm of adaptive filtering to improve the signal to noise ratio for magneto-cardiography data collected with high-temperature SQUID-based magnetometers. By frequently adjusting the adaptive parameter a go systematic optimum values in the course of the programmed procedure, the convergence is accelerated with a highest speed and the minimum steady-state error is obtained simultaneously. This algorithm may be applied to eliminate other non-steady relevant noises as well.

Optimal Size for Maximal Energy Efficiency in Information Processing of Biological Systems Due to Bistability

Energy efficiency is closely related to the evolution of biological systems and is important to their information processing. In this work, we calculate the excitation probability of a simple model of a bistable biological unit in response to pulsatile inputs, and its spontaneous excitation rate due to noise perturbation. Then we analytically calculate the mutual information, energy cost, and energy efficiency of an array of these bistable units. We find that the optimal number of units could maximize this array＇s energy efficiency in encoding pulse inputs, which depends on the fixed energy cost. We conclude that demand for energy efficiency in biological systems may strongly influence the size of these systems under the pressure of natural selection.

Optimal integration of solar home systems and appliance scheduling for residential homes under severe national load shedding

In developing countries like South Africa,users experienced more than 1030 hours of load shedding outages in just the first half of 2023 due to inadequate power supply from the national grid.Residential homes that cannot afford to take actions to mitigate the challenges of load shedding are severely inconvenienced as they have to reschedule their demand involuntarily.This study presents optimal strategies to guide households in determining suitable scheduling and sizing solutions for solar home systems to mitigate the inconvenience experienced by residents due to load shedding.To start with,we predict the load shedding stages that are used as input for the optimal strategies by using the K-Nearest Neighbour(KNN)algorithm.Based on an accurate forecast of the future load shedding patterns,we formulate the residents’inconvenience and the loss of power supply probability during load shedding as the objective function.When solving the multi-objective optimisation problem,four different strategies to fight against load shedding are identified,namely(1)optimal home appliance scheduling(HAS)under load shedding;(2)optimal HAS supported by solar panels;(3)optimal HAS supported by batteries,and(4)optimal HAS supported by the solar home system with both solar panels and batteries.Among these strategies,appliance scheduling with an optimally sized 9.6 kWh battery and a 2.74 kWp panel array of five 550 Wp panels,eliminates the loss of power supply probability and reduces the inconvenience by 92%when tested under the South African load shedding cases in 2023.

Optimizing the Layout of Rectangular Hull Tiles

Rectangular tiles can be laid on a ship's hull for protection, but the sides of the tiles must be adjusted so adjacent tiles will conform to the curvature of the hull.A method for laying tiles along a reference line was proposed, and an allowable range of displacement for the four vertices of the tile was determined.Deformations of each tile on a specific reference line were then obtained.It was found that the least deformation was required when the tiles were laid parallel to a line with the least curvature.After calculating the mean curvature on the surface, the surface was divided into three layout areas.A set of discrete points following the least deformation of the principal curvatures was obtained.A NURBS interpolation curve was then plotted as the reference line for laying tiles.The optimum size of the tiles was obtained, given the allowable maximum deformation condition.This minimized the number of bolts and the amount of stuffing.A typical aft hull section was selected and divided into three layout areas based on the distribution of curvature.The optimum sizes of rectangular tiles were obtained for every layout area and they were then laid on the surface.In this way the layout of the rectangular tiles could be plotted.

Structural optimization design of a bolster based on a simulation-driven design

A simulation-driven design method which uses multiple optimization methods can effectively promote innovative structural design tion analysis can enormously improve the efficiency of modelling and solving.This study establishes a general workflow of structural and reduce the product development cycle.Meanwhile,the sub-model technology which has more detailed simulation and optimizaoptimization for a stainless-steel metro bolster by combining the simulation-driven design method and sub-model technology.In the sub-model definition phase,the end underframe sub-model which contains the bolster is obtained based on the whole car body finite element(FE)model,and the effectiveness of the end underframe sub-model is also proved.In the conceptual design phase,the is determined according to manufacturing processes and design experiences.In the detailed design phase,the thickness of each topology path inside the bolster is obtained by the topology method and the optimized structure of the inner ribs inside the bolster part of the bolster is determined by size optimization.The simulation analyses indicate that the requirements of static strength and can be decreased by 17.79% compared with the original bolster structure,which means that not only the lightweight design goal fatigue strength are fulfilled by the optimized bolster structure.Besides,the weight can be reduced by 11.18% and the weld length is achicved.but also the welding auantity and manufacturing difficulty are geatly reduced.The results show the effectiveness of the simulation-driven design method based on the sub-model technology in the structural optimization for key parts of rail transit vehicles.

Timetable optimization for single bus line based on hybrid vehicle size model

This study proposes a flexible timetable optimization method based on hybrid vehicle size model to tackle the bus demand fluctuations in transit operation. Three different models for hybrid vehicle, large vehicle and small vehicle are built in this study, respectively. With the operation data of Shanghai Transit Route 55 at peak and off-peak hours, a heuristic algorithm was proposed to solve the problem. The results indicate that the hybrid vehicle size model excels the other two modes both in the total time and total cost. The study verifies the rationality of the strategy of hybrid vehicle size model and highlights the importance of the adaptive vehicle size in dealing with the bus demand fluctuation. The main innovation of the study is that unlike traditional timetables, the arrangement of the scheduling interval and the corresponding bus type or size are both involved in the timetable of hybrid vehicle size bus mode, which will be more effective to solve the problem of passenger demand fluctuation. Findings from this research would provide a new perspective to improve the level of regular bus service.

Research on infiltration clogging effect and its application prospect in anti-seepage project

Clogging effect,as a new concept in geological engineering,is a phenomenon of permeability decreasing under seeping in reservoir dam foundation of the alluvial and diluvial deposits with deep and thick layer,coarse particle and high permeability in mountains-gully rivers of Tibetan Plateau.A clogging infiltration instrument has been designed successfully and a series of simulation tests have been done.Based on large amounts of data,it is confirmed that the existence of the clogging effect and the law of infiltration clogging is found out.Three indexes are proposed such as "optimal size of particle","optimal size range of particle" and "characteristic pore",which are closely related with effect of infiltration clogging.The concept and results can offer a new idea to solve problems on anti-seepage of dam foundation in mountains-gully rivers environment and to study artificial clogging,meanwhile supplement of the concept of seepage deformation.

Multi-objective planning model for simultaneous reconfiguration of power distribution network and allocation of renewable energy resources and capacitors with considering uncertainties

This research develops a comprehensive method to solve a combinatorial problem consisting of distribution system reconfiguration, capacitor allocation, and renewable energy resources sizing and siting simultaneously and to improve power system's accountability and system performance parameters. Due to finding solution which is closer to realistic characteristics, load forecasting, market price errors and the uncertainties related to the variable output power of wind based DG units are put in consideration. This work employs NSGA-II accompanied by the fuzzy set theory to solve the aforementioned multi-objective problem. The proposed scheme finally leads to a solution with a minimum voltage deviation, a maximum voltage stability, lower amount of pollutant and lower cost. The cost includes the installation costs of new equipment, reconfiguration costs, power loss cost, reliability cost, cost of energy purchased from power market, upgrade costs of lines and operation and maintenance costs of DGs. Therefore, the proposed methodology improves power quality, reliability and security in lower costs besides its preserve, with the operational indices of power distribution networks in acceptable level. To validate the proposed methodology's usefulness, it was applied on the IEEE 33-bus distribution system then the outcomes were compared with initial configuration.