One of the most important issues in supply chain management, is integration of the supply chain to reduce the cost of the entire chain. In this study, a nonlinear mathematical mixed integer programming model consists of two levels of the supply chain including manufacturing plants and distribution centers have been investigated. The aim is determining orders sequencing on a single machine and allocating orders to flights so that the cost of production, transportation and earliness and tardiness penalties is minimized. In our model, factory can also carry some orders that remain of his planned flight by a charter flight whit additional transportation costs. Due to the inherent complexity of combinatorial optimization problems especially production scheduling, using hurestic methods is an appropriate approach to generating acceptable solution. Therefore, two effective meta-heuristic methods inclouding simulated annealing and discrete particle swarm optimization were developed. In addition, by using Taguchi experimental design, the algorithm parameters of the algorithms are tuned. Finally, the proposed algorithms considering two criteria, quality and hitting time, were compared and discussed
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