Toward smart logistics: A new algorithm for a multi-objective 3D bin packing problem

The most important logistics requirements are the reception of the product on time, in the right place and in the best condition. These requirements may be satisfied by implementing a smart logistic process. One important problem that is faced in that process is the bin packing problem. The bin packing is an NP-hard problem which focuses on optimizing the number of bins for a set of items with varying volumes and/or weights. Bin packing problem is used in many applications such as job scheduling, shipping items and placing data on multiple disks. Although many algorithms have been developed to solve the bin-packing problem, some drawbacks have remained unsolved like efficiency of the algorithm vs. optimal number of bins. In this research, we propose a multi-objective 3D bin packing algorithm that focuses on optimizing the number of bins as well as balancing the weight inside each bin. The proposed algorithm was implemented and tested with data gathered from FedEx. The computational results showed that the algorithm is efficient for a small number of problems and runs very fast for up to around 25000 items. The algorithm also balances the weights between the bins almost perfectly.