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Optimizing Fixed Shelf Order-Picking for AS/RS Based on Immune Particle Swarm Optimization Algorithm

机译：基于免疫粒子群算法的AS / RS固定货架拣选优化

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摘要

To avoid the disadvantage of getting into local optimum solution with particle swarm optimization in solving order-picking scheduling problem for an Automated Storage/Retrieval System(AS/RS), commutators and commutative orders are introduced into particle swarm optimization algorithm. Combining immune algorithm with particle swarm optimization algorithm, optimized populations are vaccinated and immunized. Vaccinating bacterin can improve adaptability of particles, and immune selection can prevent degeneracy of populations. The corresponding processes of the combinative algorithm are given in succession. In order to verify the above combinative algorithm, an example is presented. The calculated results show that the algorithm is operable and versatile. In solving the fixed shelf order-picking scheduling problem, the optimized solution can be found fast, simply and exact with presented algorithm.
机译：为了解决自动存储/检索系统（AS / RS）的拣选调度问题，采用粒子群优化方法进入局部最优解的弊端，将换向器和交换阶数引入了粒子群优化算法。结合免疫算法和粒子群优化算法，对优化种群进行了免疫接种。接种细菌素可以提高颗粒的适应性，而免疫选择可以防止种群的退化。依次给出组合算法的相应过程。为了验证上述组合算法，给出了一个例子。计算结果表明该算法是可行的和通用的。在解决固定货架拣货调度问题时，采用本文提出的算法可以快速，简单，准确地找到优化的解决方案。

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