Picker routing optimization of storage stacker based on improved multi-objective iterative local search algorithm

Abstract

<p style='text-indent:20px;'>In the process of warehouse automation, the efficient picker routing strategy is one of the key factors to improve warehouse efficiency. According to the order and the picking characteristics of the warehouse stacker, the picker routing of the stacker is regarded as the prize-collecting vehicle routing problem (PCVRP). According to the path and order for stacker picking, we designed a picker routing optimization strategy based on improved multi-objective iterative local search (IMOILS) algorithm. An elite pool strategy was set to save the high-quality solutions in the iterative process, and the nondominated solutions in the iterative evolution were stored and updated. Adding the adaptive enhanced perturbation strategy was beneficial to the current solution to escape from local optimum. In the local search procedure, to limit the excessively large search space, the epsilon constraint was adopted to limit the significant deterioration in another objective direction. The computational results showed that the proposed algorithm is superior to the comparison algorithms in the number of nondominated solutions, the hypervolume, and the spacing metric, and the stability of the algorithm is also good, which not only verifies the effectiveness of the proposed algorithm, but also provides a feasible optimization scheme for the storage stacker's picker routing problem.</p>

Research on maximum power point tracking algorithm of photovoltaic power generation based on improved atom search optimization algorithm

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