Article ID Journal Published Year Pages File Type
980674 Procedia Economics and Finance 2016 11 Pages PDF
Abstract

Supply chain network makes it possible to create an effective and helpful context for managing supply chain. This network is a series of equipments that play roles in the supply chain development. In this network exist producers of raw materials and product-making factories, centers of distributing products and customers. The aim of the network is minimizing the total cost so that customer's demands might be answered. In this paper, three-phase multi-product supply chain network model is presented. The super-innovative method of genetic algorithm is used to solve these problems since they are classified into NP-Hard problems. Encoding of this presented. The super-innovative method of genetic algorithm is used to solve these problems since they are classified into NP-Hard problems. Encoding of this genetic algorithm is based on priority-centered encoding. In this method, the network nodes are developed according to their priority. Some types of problems are posed that are solved by means of genetic algorithm and mathematic programming problem solving software (LINGO) and then the results are compared. Moreover, this algorithm is shown to give acceptable answers and is therefore suitable for solving the problems in three-phase multi-product supply chain network.

Related Topics
Social Sciences and Humanities Economics, Econometrics and Finance Economics and Econometrics