Optimization of 3D Constrained Rectangular Bin Packing Problem Using Recursive Ant Colony Algorithm

This research presents an application of Ant colony optimization meta-heuristic to the bin packing problems. Hybridization of Ant tuning strategy has introduced to improve the results obtained from basic ant system by utilizing the behaviour of artificial ants to perform local search. The objective is to pack the arbitrary sized three dimensional rectangular prismatic bins into the container of standard sizes in such a way that the empty space inside the container should be least as minimum. The bins should be packed by satisfying the packing constraints such as placement constraint, overlapping constraint, shipment placement constraint, stability constraint, etc. The output from the ants algorithm have been further optimized and decoded to the user understandable graphical format using heuristic Ant tuning algorithm. Experiments using well-known benchmark bin packing problems show that this approach improves on the performance and is competitive with other evolutionary in computational time also.