Scheduling an Integrated Production and Air Transportation in Supply Chain with Sequence-Dependent Setup Times

This paper presents a new mathematical programming model for an integrated production and air transportation in supply chain management with sequence-dependent setup times in order to design an applied procedure for the production and distribution schedule. The aim of this model is to minimize the total supply chain cost consisting of the costs of distribution, production earliness and tardiness, and delivery. Because of the complexity and NP-hardness of this problem, two meta-heuristics based on genetic algorithm (GA) and variable neighborhood search (VNS) are proposed. The parameters of these algorithms and their appropriate operators are set and determined by the use of the Taguchi experimental design. Then, the quality of the results obtained by these algorithms is compared. The computational results show that the developed VNS outperforms the proposed GA.