Design of integrated information system and supply chain for selection of new facility and suppliers by a unique hybrid meta-heuristic computer simulation algorithm

Abstract

This research concentrates on integrated modeling of supply chain and information system through a unique integrated meta-heuristic computer simulation algorithm. It uses computer simulation and genetic algorithm in order to select suppliers and new facilities by reducing delivery time and final production cost. To reach these goals, this research has simulated an actual case study with simulation and in the other stages, has moved forward to improve and optimize the objectives by focusing on selection of suppliers. It also uses the collective information to reduce total cycle time and cost simultaneously. Moreover, a dynamic model is designed to determine the status of new facilities. The dynamic model is solved by genetic algorithm focusing on the time and cost reduction as the main objectives of the problem. Results show the effectiveness of the integrated algorithm. This is the first study that uses a hybrid meta-heuristic approach for integrated design of information system and supply chain.