#5784. An M/M/c queue model for vehicle routing problem in multi-door cross-docking environments

July 2026publication date
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Journal’s subject area:
Modeling and Simulation;
Management Science and Operations Research;
Computer Science (all);
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Abstract:
Cross-docking is a strategy to facilitate a persistent process from suppliers to the consumer points, without long-term storage of products at a distribution warehouse. Products are collected from various origins by inbound trucks, unloaded to the cross-dock, reconsolidated with other products, and finally loaded onto outbound trucks within the same or next day. Because of the limited number of dock-doors as the main resources and the uncertain arrival time of trucks at the cross-dock, queue problems in such environments are unavoidable. This study considers a vehicle routing problem (VRP) for a multi-door cross-docking system with a queuing approach. A real application of the proposed model can be found in congestion conditions at the cross-docking yard, when the queuing time of the vehicles (i.e., the queuing delay) may reduce the quality of service. Moreover, in some cases, improper queue management at a facility such as a cross-dock may incur an economic cost associated with the waiting time in the queue. In this study, we focus on the receiving doors of a cross-dock and assume that the rate of truck arrivals at the cross-dock is a random variable. Moreover, the cross-dock is not able to provide service to all vehicles simultaneously; it has some limitations such as capacity constraints and service time restrictions. Thus, an M/M/c queuing formulation is proposed to model this cross-docking environment, in which the vehicles’ dispatch plan for starting the pickup process would also be determined. In the proposed multi-channel queuing system, the arrival flow of trucks to the cross-docking terminal can be deemed as a Poisson process, resulting in a nonlinear mathematical formulation to optimize the problem. The model is then linearized. To handle its computational complexity, we develop a new Genetic Algorithm (GA) to obtain near-optimal solutions to the problem and compare them with those of the optimization software GAMS. Then, a sensitivity analysis is done on different parameters of the model, and their effect on transportation cost and waiting cost of vehicles in the queue is investigated.
Keywords:
Congestion; Genetic algorithm; Multi-door cross-docking; Multi-products; Queuing theory; Vehicle routing problem

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