3d Arbitrary Sized Bin Packing Optimization Using 2pdc Heuristic: A Adaptive Genetic Approach

This paper presents a Heuristic Genetic Algorithm (HGA) for optimizing three dimensional (3D) arbitrary sized heterogeneous boxes into a container, by considering practical constraints facing in the shipment container loading industries. Objective of this research is to pack heterogeneous boxes of varying length, width and height into a container of standard dimension, without violating major practical constraints to obtain a real time feasible packing pattern and also adaptive in nature. HGA is developed to maximize the container volume utilization and inturn profit. It significantly improves the search efficiency with less computational time and loads most of the heterogeneous boxes into the container by considering its optimal position and orientation. In general, HGA in comparison with the traditional genetic algorithm is substantially better and more satisfactory.