摘要
针对自动化立体仓库库区分配优化问题建立了堆垛机平均运行时间模型,为求出其最优解,提出一种改进型细菌觅食算法。在求最优解的过程中,根据当前全局最优解和局部最优解,分阶段对趋化步长进行自适应调整;同时根据细菌个体对种群多样性的贡献率对其迁移概率进行设定,不但提高了收敛速度,而且保证了寻优的全局性。结合工业现场实例与原始细菌觅食算法和遗传算法进行了仿真对比,结果表明所提算法在解的质量及收敛速度上都具有明显的优势。
For automated warehouse area allocation optimization problem, an average run time model of stacker was built. To get its optimal solution, an improved bacterial foraging algorithm was proposed. In the process of warehouse area allocation optimization, chemotactic stepsize was adjusted adaptively based on current global and local op timal. The elimination and dispersal probability of individual bacteria was set according to the level of contributing to diversity of population simultaneously. It not only enhanced the convergence efficiency, but also ensured the global optimization. The basic bacterial foraging algorithm and genetic algorithm was compared through the industrial real case, and the results showed that the proposed algorithm achieved better performance in terms of the solution quality and the convergence efficiency.
出处
《计算机集成制造系统》
EI
CSCD
北大核心
2014年第7期1684-1690,共7页
Computer Integrated Manufacturing Systems
基金
国家自然科学基金资助项目(61074032
61273040)
上海市科委重点基础资助项目(10JC1405000)
上海市青年科技启明星计划资助项目(12QA1401100)
上海市教委创新基金资助项目(12YZ020)~~
