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

Jose Alejandro Cano (), Pablo Cortés, Jesús Muñuzuri and Alexander Correa-Espinal
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Jose Alejandro Cano: Universidad de Medellín
Pablo Cortés: Universidad de Sevilla
Jesús Muñuzuri: Universidad de Sevilla
Alexander Correa-Espinal: Universidad Nacional de Colombia

Flexible Services and Manufacturing Journal, 2023, vol. 35, issue 2, No 4, 376-415

Abstract: 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.

Keywords: Order picking; Picker routing problem; Ant colony optimization; Genetic algorithms; Warehouse management; High-level warehouses (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (1)

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DOI: 10.1007/s10696-022-09445-y

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