| 基于改进混合作用力微粒群算法的液压阀块加工车间调度优化 |
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| 引用本文： | 陈东宁,彭晓静,姚成玉,张晓磊,杨晓荣. 基于改进混合作用力微粒群算法的液压阀块加工车间调度优化[J]. 液压与气动, 2019, 0(8): 6-12. DOI: 10.11832/j.issn.1000-4858.2019.08.002 |
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| 作者姓名： | 陈东宁 彭晓静 姚成玉 张晓磊 杨晓荣 |
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| 作者单位： | 1. 燕山大学河北省重型机械流体动力传输与控制重点实验室， 河北秦皇岛066004;2. 先进锻压成形技术与科学教育部重点实验室(燕山大学)， 河北秦皇岛066004;3. 燕山大学河北省工业计算机控制工程重点实验室， 河北秦皇岛066004 |
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| 基金项目： | 国家自然科学基金(51405426)；河北省自然科学基金(E2016203306)；中国博士后科学基金(2017M621101) |
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| 摘 要： | 针对微粒群算法作用力规则的不足,提出改进混合作用力微粒群(IHFPSO)算法。采用阶段性搜索策略,将算法的搜索过程分为前期和后期2个搜索阶段:在前期搜索阶段,微粒在其他微粒的引斥力作用下进行最优搜索,以保持种群多样性;在后期搜索阶段,微粒在双引力及引力提供的加速度的共同作用下向最优解收敛,以提高局部搜索能力。将所提出的IHFPSO算法应用于液压阀块加工车间调度问题,利用矩阵变量来处理约束条件,给出一种基于矩阵的微粒编码、解码方法。通过液压阀块加工车间调度优化实例,将IHFPSO算法与微粒群算法、中值导向微粒群算法、扩展微粒群算法、多作用力微粒群算法进行对比,验证提出的IHFPSO算法结果最优,实现液压阀块加工车间调度优化。
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| 关 键 词： | 混合作用力 微粒群算法 液压阀块 车间调度 |
| 收稿时间： | 2018-08-31 |
Hydraulic Manifold Shop Scheduling Optimization Based on Improved Hybrid Force Particle Swarm Optimization Algorithm |
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| CHEN Dong-ning,PENG Xiao-jing,YAO Cheng-yu,ZHANG Xiao-lei,YANG Xiao-rong. Hydraulic Manifold Shop Scheduling Optimization Based on Improved Hybrid Force Particle Swarm Optimization Algorithm[J]. Chinese Hydraulics & Pneumatics, 2019, 0(8): 6-12. DOI: 10.11832/j.issn.1000-4858.2019.08.002 |
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| Authors: | CHEN Dong-ning PENG Xiao-jing YAO Cheng-yu ZHANG Xiao-lei YANG Xiao-rong |
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| Affiliation: | 1. Hebei Provincial Key Laboratory of Heavy Machinery Fluid Power Transmission and Control,Yanshan University, Qinhuangdao, Hebei066004;2. Key Laboratory of Advanced Forging & Stamping Technology and Science (Yanshan University),Ministry of Education of China, Qinhuangdao, Hebei066004;3. Key Laboratory of Industrial Computer Control Engineering of Hebei Province, Yanshan University, Qinhuangdao, Hebei066004 |
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| Abstract: | Aimed at defects of attraction and repulsion rules of PSO algorithm, an IHFPSO algorithm is proposed. Using a staged search strategy, the search process of algorithm is divided into earlier and later stages. At the earlier-stage, each particle searches the optimum under attraction and repulsion produced by all particles, to maintain population diversity; At the later-stage, particles converge to the optimal solution under the effect of double attraction and acceleration provided by the attraction, which is to improve local searching ability. The proposed IHFPSO algorithm is applied in hydraulic manifold processing shop scheduling problem, and a particle encoding and decoding method is presented based on matrix, which makes use of matrix variables to deal with constraints of problem. IHFPSO algorithm shows better performance compared with PSO algorithm, MPSO algorithm, EPSO algorithm and MFPSO algorithm in optimizing manifold processing shop scheduling problem, and it realizes the optimization of hydraulic manifold shop scheduling. |
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| Keywords: | hybrid force PSO algorithm hydraulic manifold shop scheduling |
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