Selective Breeding Model for Optimizing Multi Container Loading Problems with Practical Constraints

Abstract

Abstract Multi container loading problem have been considered in this research for optimization of its packing pattern to yield maximum utilization of the container volume by satisfying the practical constraints such as boundary crossing constraint, weight constraint, stability constraint and placement constraint using selective breading algorithm. To be useful in real time packing, developed model also checks the feasibility of packing pattern and also uses best fit tuning algorithm for forbid possible empty spaces inside the container with the available bins and thereby avoid cargo displacements at the travel. The boundary crossing constraint conforms that the pallets are completely packed inside the containers without any overlap between themselves and with container boundary. Weight constraints are to check the total weights of the bins to be packed are within the threshold limit. Stability constraint is to satisfy the centre of gravity of the cargo is in line with the container and also the load bearing capacity of the bins. Placement constraint is to build pallets by considering the ease in loading and unloading respectively. In order to validate the developed model, the computational study had performed with large number of instances from ORLIB and the obtained solutions were satisfactory in most cases.