An instance generator for the multi-objective 3D packing problem

Abstract

Cutting and packing problems have important applications to the transportation of cargo. Many algorithms have been proposed for solving the 2D/3D cutting stock problems but most of them consider single objective optimization. The goal of the problem here proposed is to load the boxes that would provide the highest total volume and weight to the container, without exceeding the container limits. These two objectives are conflicting because the volume of a box is usually not proportional to its weight. This work deals with a multi-objective formulation of the 3D Packing Problem (3DPP). We propose to apply multi-objective evolutionary algorithms in order to obtain a set of nondominated solutions, from which the final users would choose the one to be definitely carried out. For doing an extensive study, it would be necessary to use more problem instances. Instances to deal with the multi-objective 3DPP are non-existent. For this purpose, we have implemented an instance generator.