Abstract
Production distribution network (PDN) planning problems in multi echelon status are commonly complex with dynamic relationships that cause several uncertainties in different parameters of the network. In this paper, we formulate a multi echelon PDN to deliver products to customers with uncertain demand in the least time with uncertain delivery lead time. The proposed network is including multi supplier, producer, potential depot, retailer and inland and outland customer in multi time period horizon. A stochastic multi objective model with maximizing total profit of the system and minimizing total delivery lead time is designed. We apply chance constraints approach to cover the uncertainty of the model and introduce two heuristic methods named selective firefly algorithm (SFA) and ranking genetic algorithm (RGA) in order to solve several sized especially real world instances. Finally, the performance of two proposed algorithms is examined with solving several sized instances. The results indicate average improvement 6.12% and 8.93% with applying SFA and RGA, respectively.
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