Genetic algorithms for door-assigning and sequencing of trucks at distribution centers for the improvement of operational performance

In a supply chain, cross docking is one of the most innovative systems for improving the operational performance at distribution centers. By utilizing this cross docking system, products are delivered to the distribution center via inbound trucks and immediately sorted out. Then, products are shipped to customers via outbound trucks and thus, no inventory remains at the distribution center. In this paper, we consider the scheduling problem of inbound and outbound trucks at distribution centers. The aim is to maximize the number of products that are able to ship within a given working horizon at these centers. In this paper, a mathematical model for an optimal solution is derived and intelligent genetic algorithms are proposed. The performances of the genetic algorithms are evaluated using several randomly generated examples.

► We consider truck scheduling problem at distribution centers with cross docking.
► A mixed integer programming model is derived in search for the optimal solution.
► We propose three genetic algorithms to increase solution efficiency.
► Genetic algorithm with dispatching rule provides the highest quality performance.