This paper aims at formulating a Picking Routing Problem with K homogenousmaterial handling equipment for a refrigerated warehouse (PRPHE). Discrete particleswarm optimization (PSO) and genetic algorithm (GA) metaheuristics are developed andvalidated for solving PRPHE. The discrete PSO is a novel approach to solving cold routingpicking problems, which has not been detected in the scientific literature and is considered acontribution to the state of the art. The main difference between classical and discrete PSOis the structure and algebraic formulation of the positions and velocities of the particles,which are discrete rather than continuous under our approach. A full factorial design wasdeveloped with the following four factors: picking routing metaheuristic (PRM), depot, pickinglist size (PLS) and homogeneous material handling equipment (MHE). Based on the resultsof the experimental analysis, we identified that GA metaheuristics generated better solutionsthan discrete PSO for PRPHE. These statistical results demonstrated that GA metaheuristicsproduced time savings of between 22.89 and 86.75 seconds per set of cold picking routes,as well as an increase in the operational efficiency of between 1.98 and 2.81%, as comparedwith PSO discrete. Finally, it should be noted that this paper is one of the first in tacklingpicking routing in a refrigerated warehouse, thereby contributing to knowledge in this field.