A Multi-Start Biased-Randomized Algorithm for Solving The 3-Dimensional Case Picking Problem

This paper introduces the 3-dimensional case picking problem (3D-CPP) and proposes an algorithm to solve it. The 3D-CPP combines two important topics in modern warehouse logistics: the pallet loading problem and the routing of pickers in manual warehouses. The proposed optimization procedure aims at minimizing the overall distance traveled by the pickers, and is achieved by combining a routing problem (i.e., the order in which picking positions are visited) with a loading problem (i.e., the way in which cases are placed onto the pallet). We also consider additional constraints regarding the weight, vertical support, and strength of the cases. We first propose a constructive heuristic which combines routing and packing procedures, then extend it into a multi-start biased-randomized algorithm. A series of computational experiments assess the proposed approach, both by comparison with other algorithms as well as with real-life data provided by an industrial partner