针对多货叉仓库调度优化问题,提出一种改进型细菌觅食算法。首先,分阶段对趋化步长进行自适应调节,引导搜索沿最优方向进行;其次,提出基于个体种群多样性贡献率的启发式迁移策略,降低进入局部最优的机率;再次,采用不可行解部分保留策略以增加求出最优解的机会;最后,对该算法的收敛性进行证明,并结合工业现场调度问题对其性能进行验证。算例结果表明,所提出的算法对多货叉仓库调度优化问题在解的质量及收敛速度上都取得了较好效果。
For the automated warehousing scheduling problem with multi-shuttles, an improved bacterial foraging algorithm is proposed. Firstly, the chemotactic stepsize is adaptively adjusted to guide search toward the optimum solution. Then, the heuristic elimination and dispersal strategy is devised based on the level of individual contributing rate to the diversity of population, which reduces the probability of falling into local optimum. The strategy of preserving some of infeasible solutions is adopted to increase the chances of obtaining the optimal solution. Finally, the convergence of the proposed algorithm is proved and the performance is tested through simulation combined with the industrial real world case. Results show that the proposed algorithm achieves better performance in terms of the solution quality and the convergence efficiency for the automated warehousing scheduling problem with multi-shuttles.