Solving the picker routing problem in multi-block high-level storage systems using metaheuristics

Jose Alejandro Cano, Pablo Cortés, Jesús Muñuzuri, Alexander Correa-Espinal

Research output: Contribution to journalArticlepeer-review

Abstract

This study aims to minimize the travel time in multi-block high-level storage systems considering height level constraints for picking devices to leave aisles. Considering these operating environments, the formulation of minimum travel times between each pair of storage positions is proposed and the picker routing problem (PRP) is solved by means of Genetic Algorithms (GA) and Ant Colony Optimization (ACO). A parameter tuning is performed for both metaheuristics, and the performance of the GA and ACO is compared with the optimal solution for small-sized problems demonstrating the reliability of the algorithms solving the PRP. Then, the performance of the GA and ACO is tested under several warehouse configurations and pick-list sizes obtaining that both metaheuristics provide high-quality solutions within short computing times. It is concluded that the GA outperforms the ACO in both efficiency and computing time, so it is recommended to implement the GA to solve the PRP in joint order picking problems.

Original languageEnglish
JournalFlexible Services and Manufacturing Journal
DOIs
StateAccepted/In press - 2022

Keywords

  • Ant colony optimization
  • Genetic algorithms
  • High-level warehouses
  • Order picking
  • Picker routing problem
  • Warehouse management

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