Comparison of advanced methods for picking path optimization: Case study of dual-zone warehouse

Abstract

Minimizing the travel distance of a picking tour is often considered an imperative factor in improving warehouse operation efficiency. This paper concentrates on the performance of the genetic algorithm (GA) method and its comparison to other routing strategies such as heuristics, the experienced warehouse picker and the brute-force algorithm under given assumptions. The set of simulations and calculations is based on an industrial case example. The results of the investigated routing strategies under given assumptions (middle size dual-zone warehouse, order size – 15 items, etc.) show the dominance of the brute-force algorithm in comparison to the experienced picker, GA and simple heuristics. It also indicates that GA is an optimization method which needs modification in dealing with picking path optimization problems and under given assumptions could generate better solutions than simple heuristics and comparable to experienced picker. The results also show quite significant sensitivity of GA results on used selection operator, size of population and number of generations. (Received in May 2020, accepted in August 2020. This paper was with the authors 1 month for 1 revision.).