Presenting a bi-objective integrated production – distribution planning problem model in a multi echelon supply chain with considering service level

Abstract

In this paper, a bi-objective integrated of production distribution planning problem model in a multi echelon supply chain is presented. This model is considered in a four echelon supply chain includes suppliers, manufactures, distribution centers and customers with several types of raw material and product in multi-time period. In addition to minimize the total cost of supply chain including transportation and supply of materials costs, preparation and production of products, inventory holding of materials and products in manufacture and distribution centers, transportation and purchase of products for distributors and customers, and backorder cost, the second objective is to decrease the transfer time of products in order to increasing the service level for customers. Two Pareto-based multi-objective meta-heuristic algorithms namely non-dominated sorting genetic algorithm (NSGA-II) and non-dominated ranking genetic algorithm (NRGA) are proposed to solve the model. Since the solution quality of all meta-heuristic algorithms severely depended on their parameters, Taghuchi method has been utilized to tune the parameters of algorithms. Finally, computational results obtained by implementing the algorithms on several problems of different sizes demonstrate the performance of proposed methodologies.

Keywords

• Multi-Objective Production-Distribution Planning
• Non-dominated Ranking Genetic Algorithm
• Non-dominated Sorting Genetic Algorithm
• supply chain
• Taghuchi Method