Addressing the Freight Consolidation and Containerization Problem by Recent and Hybridized Meta-heuristic Algorithms

Nowadays, in global free market, third-party logistics providers (3PLs) are becoming increasingly important. Hence, this study aims to develop the freight consolidation and containerization problem, which consists of loading items into containers and then shipping these containers to different warehouse from they are delivered to their final destinations. In order to handle the proposed problem, this research is not only used the traditional and recent algorithms, but also the two new hybridized methods are introduced in order to strength of advantages of recent ones. In this regard, this study considers the two important phases in meta-heuristic to develop new ones. Besides, Taguchi experimental design method is utilized to set and estimate the proper values of the algorithms’ parameters to improve their performance. For the purpose of performance evaluation of the proposed algorithms, various problem sizes are employed and the computational results of the algorithms are compared with each other. Finally, the impacts of the rise in the problem size on the performance of the proposed algorithms are investigated.

Keywords:

Freight consolidation and containerization problem , Red Deer algorithm , Stochastic Fractal search , Hybridized methods , Intensification and diversification phases