Designing a mathematical model for the multi-product green supply chain of automobile industry under uncertainty

Subject Areas : Futurology

davood khodadadian ¹ , reza radfar ² , abbas toloieashlaghi ³

1 - Ph.D. student of industrial management, Islamic Azad University, Science and Research Branch, Tehran, iran
2 - Full Professor, faculty of management and economics, Industrial management department, science and research branch, Tehran, Iran (Corresponding Author) [e-mail]
3 - Full Professor, faculty of management and economics, Industrial management department, science and research branch, Tehran, Iran

Received: 2018-01-21 Accepted : 2018-10-29 Published : 2019-01-21

Keywords: Designing Supply Chain Network, Non-dominated Sorting Genetic Algorithm, Multi-objective optimization, Green Supply,

Abstract :

Today supply chain network is recognized as the main bases in economic activity. Their significance is due to just in time delivery and the efficiency of different commodities including food, clothing, energy, computer hardware. This has stimulated researchers and experts to analyze supply chain problems. Meanwhile, uncertainty has penetrated every level of our lives and we encounter it every day. The present paper focuses on green supply chain that consider uncertainty conditions to solve a model for designing a forward green supply network (environmental)under uncertainty of future economic conditions in Iran Khodro Company. The problem of designing the aforementioned network includes hypotheses including multi-commodity, multi-layer and one-period. Due to inconsistent economic conditions, uncertainty has been differently tackled here as compared with previous literature. In this problem, several important parameters have been considered as indefinite including customers’ demands, operating expenses, the productive capacity and relocating capacity of facilities. The proposed model also considers the contamination of production section and the transportation system of the chain and tries to reduce it by suggesting an objective function and Eco-indicator 99 method. As well, production and distribution centers operate in a dual-purpose manner. Saving costs and reducing contamination due to applying transportation supplies and common infrastructures are among the benefits of this method. Considering the complexity of solving this problem and its NP-hard nature, the meta heuristic method of genetic algorithm with non-dominated sorting (NSGAII) was analyzed and finally model performance was examined with a numerical example and solving it with MATLAB and GAMS software.