| 基于遗传粒子群算法的堆垛机作业路径优化 |
| Stacker Job Path Optimization Based on Genetic Particle Swarm |
| 投稿时间：2015-05-19 |
| 中文关键词:遗传粒子群算法 自动化仓库 拣选作业 堆垛机 |
| 英文关键词:Genetic PSO automated warehouse picking operations stacker |
| 基金项目:国家自然科学基金（51275321）；河北省自然科学基金（(F2013210109）；河北省高等学校创新团队领军人才培育计划(LJRC018)；河北省教育厅自然科学青年基金 (QN2014151) |
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| 中文摘要: |
| 堆垛机的作业路径决定了自动化仓库的作业效率。建立了堆垛机作业的数学模型，并采用遗传粒子群算法对自动化仓库堆垛机作业路径进行优化。该算法引入了遗传算法中交叉和变异操作，通过粒子与个体极值和群体极值的交叉和粒子自身变异的方式来搜索最优解。仿真实验结果表明，该算法的求解效果在收敛速度和优化效果方面都有明显的提高，可以有效地减少堆垛机系统拣选作业运行时间，提高了自动化仓库的作业效率。这对实际应用有一定的参考价值。 |
| 英文摘要: |
| The route optimization of the stacker determines the operating efficiency of automatic storage and retrieval system. The mathematical model of stacker job is established, and the route optimization problem of the stacker is investigated by means of Genetic PSO. The algorithm uses genetic algorithm crossover and mutation, by particles and groups with individual extremes crossover and mutation particle itself way to search for the optimal solution. The simulation results show that, the speed and optimization convergence effect of the solving has been significantly improved, the picking operations time has been effectively reduced, and the operating efficiency of automatic storage and retrieval system has been improved, which is of reference value for practical application. |
| 刘凯,牛江川,申永军,李素娟.基于遗传粒子群算法的堆垛机作业路径优化[J].石家庄铁道大学学报(自然科学版),2016,(2):67-71. |
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