An intelligent truck scheduling and transportation planning optimization model for product portfolio in a cross-dock

Selecting an effective category of products and their distribution are a challenge in distribution centers separated in two successive stages. First, the optimal number of the products and their participation will be selected. Then, an appropriate planning for distributing and transporting the selected products is determined. Hence, this paper develops a bi-objective mathematical model to integrate truck scheduling and transportation planning in a cross-docking system in a forward/reverse logistics network. For effective products category selection, a hybrid intelligent product portfolio optimization model is proposed. To solve the bi-objective model, a hybrid of the improved version of the augmented e-constraint method (AUGMECON2) and TOPSIS is designed and utilized. Moreover, a real industrial case is provided to justify the performance and applicability of the model and the solution approach.