Truck routing and scheduling for cross-docking in the supply chain: model and solution method

Abstract

Among various distribution networks, the idea behind the cross-docking for cost reduction is to decrease/eliminate inventory to the extent possible. In classical cross-dock, it is assumed that there is one truck for each supplier and customer. Yet, one truck for each supplier and customer can be very costly and consequently ineffective. Each truck likely can serve more than one supplier/customer in its pickup/delivery process. Therefore, to more actualize the cross-dock problem, it can be extended with the truck routing problem, i . e ., the truck scheduling in the cross-docking system and truck routing in the pickup/delivery process. Hence, this paper considers the integrated truck routing and scheduling problem. First, the problem is formulated as a mixed integer linear programming model. Using this model, we solve small-sized instances to optimality. Moreover, two metaheuristics, a reactive tabu search with path relinking and a generational genetic algorithm with a local search and restart phase, are proposed to solve large instances. The parameters of the proposed algorithms are tuned. Finally, the performance of the proposed algorithms is evaluated.