Picking Routing Problem with K homogenous material handling equipment for a refrigerated warehouse

This paper aimed at formulating a Picking Routing Problem with K homogenous material handling equipment for a refrigerated warehouse (PRPHE). A discrete PSO (Particle Swarm Optimization) and Genetic Algorithm (GA) metaheuristic are developed and validated for solving PRPHE.  The discrete PSO is a novel approach for solving cold routing picking problem, which had not been, detected in the scientific literature which is considerate a contribution to the state of the art. The main difference between classical PSO and discrete one developed is the structure and algebraic formulation of the positions and velocities of the particles, which are discrete instead of being continuous.  A full factorial design with four factors named picking routing metaheuristics (PRM), depot, picking list size (PLS) and group of homogeneous Material Handling Equipment (MHE) was developed. Based on results of the experimental analysis was identified that GA metaheuristic generated betters solutions than discrete PSO for PRPHE. Therefore, these statistical results demonstrated that GA metaheuristic produced time savings between 22.89 and 86.75 seconds per set of cold picking routes as well as an increase of the operational efficiency between 1.98 and 2.81% again PSO discrete. Finally, it should be noted that this paper is one of the first in tackling picking routing in a refrigerated warehouse hence its contribution to the knowledge.