Multiple-objective genetic optimization of the spatial design for packing and distribution carton boxes

Packing and cutting problems, which dealt with filling up a space of known dimension with small pieces, have been an attractive research topic to both industry and academia. Comparatively, the number of reported studies is smaller for container spatial design, i.e., defining the optimal container dimension for packing small pieces of goods with known sizes so that the container space utilization is maximized. This paper aims at searching an optimal set of carton boxes for a towel manufacturer so as to lower the overall future distribution costs by improving the carton space utilization and reducing the number of carton types required. A multi-objective genetic algorithm (MOGA) is used to search the optimal design of carton boxes for a one-week sales forecast and a 53-week sales forecast. Clustering techniques are then used to study the order pattern of towel products in order to validate the genetically generated results.