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Parallel discrete lion swarm optimization algorithm for solving traveling salesman problem 被引量:2
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作者 ZHANG Daoqing JIANG Mingyan 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2020年第4期751-760,共10页
As a typical representative of the NP-complete problem, the traveling salesman problem(TSP) is widely utilized in computer networks, logistics distribution, and other fields. In this paper, a discrete lion swarm optim... As a typical representative of the NP-complete problem, the traveling salesman problem(TSP) is widely utilized in computer networks, logistics distribution, and other fields. In this paper, a discrete lion swarm optimization(DLSO) algorithm is proposed to solve the TSP. Firstly, we introduce discrete coding and order crossover operators in DLSO. Secondly, we use the complete 2-opt(C2-opt) algorithm to enhance the local search ability.Then in order to enhance the efficiency of the algorithm, a parallel discrete lion swarm optimization(PDLSO) algorithm is proposed.The PDLSO has multiple populations, and each sub-population independently runs the DLSO algorithm in parallel. We use the ring topology to transfer information between sub-populations. Experiments on some benchmarks TSP problems show that the DLSO algorithm has a better accuracy than other algorithms, and the PDLSO algorithm can effectively shorten the running time. 展开更多
关键词 discrete lion swarm optimization(DLSO)algorithm complete 2-opt(C2-opt)algorithm parallel discrete lion swarm optimization(PDLSO)algorithm traveling salesman problem(TSP)
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Optimization of volume to point conduction problem based on a novel thermal conductivity discretization algorithm
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作者 杜文静 王沛丽 +1 位作者 宋立鹏 程林 《Chinese Journal of Chemical Engineering》 SCIE EI CAS CSCD 2015年第7期1161-1168,共8页
A conduction heat transfer process is enhanced by filling prescribed quantity and optimized-shaped high thermal conductivity materials to the substrate. Numerical simulations and analyses are performed on a volume to ... A conduction heat transfer process is enhanced by filling prescribed quantity and optimized-shaped high thermal conductivity materials to the substrate. Numerical simulations and analyses are performed on a volume to point conduction problem based on the principle of minimum entropy generation. In the optimization, the arrangement of high thermal conductivity materials is variable, the quantity of high thermal-conductivity material is constrained, and the objective is to obtain the maximum heat conduction rate as the entropy is the minimum.A novel algorithm of thermal conductivity discretization is proposed based on large quantity of calculations.Compared with other algorithms in literature, the average temperature in the substrate by the new algorithm is lower, while the highest temperature in the substrate is in a reasonable range. Thus the new algorithm is feasible. The optimization of volume to point heat conduction is carried out in a rectangular model with radiation boundary condition and constant surface temperature boundary condition. The results demonstrate that the algorithm of thermal conductivity discretization is applicable for volume to point heat conduction problems. 展开更多
关键词 Volume to point conduction Principle of minimum entropy generation algorithm of thermal conductivity discretization optimization
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Multi-Objective Optimization of Multi-Product Parallel Disassembly Line Balancing Problem Considering Multi-Skilled Workers Using a Discrete Chemical Reaction Optimization Algorithm
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作者 Xiwang Guo Liangbo Zhou +4 位作者 Zhiwei Zhang Liang Qi Jiacun Wang Shujin Qin Jinrui Cao 《Computers, Materials & Continua》 SCIE EI 2024年第9期4475-4496,共22页
This work investigates a multi-product parallel disassembly line balancing problem considering multi-skilled workers.A mathematical model for the parallel disassembly line is established to achieve maximized disassemb... This work investigates a multi-product parallel disassembly line balancing problem considering multi-skilled workers.A mathematical model for the parallel disassembly line is established to achieve maximized disassembly profit and minimized workstation cycle time.Based on a product’s AND/OR graph,matrices for task-skill,worker-skill,precedence relationships,and disassembly correlations are developed.A multi-objective discrete chemical reaction optimization algorithm is designed.To enhance solution diversity,improvements are made to four reactions:decomposition,synthesis,intermolecular ineffective collision,and wall invalid collision reaction,completing the evolution of molecular individuals.The established model and improved algorithm are applied to ball pen,flashlight,washing machine,and radio combinations,respectively.Introducing a Collaborative Resource Allocation(CRA)strategy based on a Decomposition-Based Multi-Objective Evolutionary Algorithm,the experimental results are compared with four classical algorithms:MOEA/D,MOEAD-CRA,Non-dominated Sorting Genetic Algorithm Ⅱ(NSGA-Ⅱ),and Non-dominated Sorting Genetic Algorithm Ⅲ(NSGA-Ⅲ).This validates the feasibility and superiority of the proposed algorithm in parallel disassembly production lines. 展开更多
关键词 Parallel disassembly line balancing problem multi-product multiskilled workers discrete chemical reaction optimization algorithm
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Dynamic Weapon Target Assignment Based on Intuitionistic Fuzzy Entropy of Discrete Particle Swarm 被引量:17
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作者 Yi Wang Jin Li +1 位作者 Wenlong Huang Tong Wen 《China Communications》 SCIE CSCD 2017年第1期169-179,共11页
Aiming at the problems of convergence-slow and convergence-free of Discrete Particle Swarm Optimization Algorithm(DPSO) in solving large scale or complicated discrete problem, this article proposes Intuitionistic Fuzz... Aiming at the problems of convergence-slow and convergence-free of Discrete Particle Swarm Optimization Algorithm(DPSO) in solving large scale or complicated discrete problem, this article proposes Intuitionistic Fuzzy Entropy of Discrete Particle Swarm Optimization(IFDPSO) and makes it applied to Dynamic Weapon Target Assignment(WTA). First, the strategy of choosing intuitionistic fuzzy parameters of particle swarm is defined, making intuitionistic fuzzy entropy as a basic parameter for measure and velocity mutation. Second, through analyzing the defects of DPSO, an adjusting parameter for balancing two cognition, velocity mutation mechanism and position mutation strategy are designed, and then two sets of improved and derivative algorithms for IFDPSO are put forward, which ensures the IFDPSO possibly search as much as possible sub-optimal positions and its neighborhood and the algorithm ability of searching global optimal value in solving large scale 0-1 knapsack problem is intensified. Third, focusing on the problem of WTA, some parameters including dynamic parameter for shifting firepower and constraints are designed to solve the problems of weapon target assignment. In addition, WTA Optimization Model with time and resource constraints is finally set up, which also intensifies the algorithm ability of searching global and local best value in the solution of WTA problem. Finally, the superiority of IFDPSO is proved by several simulation experiments. Particularly, IFDPSO, IFDPSO1~IFDPSO3 are respectively effective in solving large scale, medium scale or strict constraint problems such as 0-1 knapsack problem and WTA problem. 展开更多
关键词 intuitionistic fuzzy entropy discrete particle swarm optimization algorithm 0-1 knapsack problem weapon target assignment
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Smart Clothing Fabric Color Matching with Reference to Popular Colors
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作者 ZHANG Yani ZHUANG Jianqiang +2 位作者 HUANG Rong DONG Aihua YUAN Haodong 《Journal of Donghua University(English Edition)》 CAS 2022年第4期317-324,共8页
Color economy and market fashion trend have an increasing impact on clothing fabric color matching.Therefore,a smart clothing fabric color matching system with reference to popular colors is designed to realize the di... Color economy and market fashion trend have an increasing impact on clothing fabric color matching.Therefore,a smart clothing fabric color matching system with reference to popular colors is designed to realize the diversification of clothing color matching,which includes a palette generation module and a clothing fabrics-palette color matching network(CF-PCN).Firstly,palette generation module generates palettes referring popular colors while maintains color styles of clothing fabrics.Secondly,CF-PCN generates color matching images containing color information of palettes.The experimental results show that the color matching system has a higher average pixel ratio of palette colors and contains more palette color information.It demonstrates that the system achieves color matching innovation referring popular colors while retaining color style of clothing brands and provides designers with appropriate color matching solutions. 展开更多
关键词 popular color clothing fabric color matching support vector machine(SVM) discrete particle swarm optimization algorithm generative adversarial network
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