Title of article :
Sustainable Supplier Selection and Order Allocation Applying Metaheuristic Algorithms
Author/Authors :
Arabsheybani, Amir Industrial Engineering Department - Faculty of Engineering - Babol Noshirvani University of Technology, Babol, Iran , Paydar, Mohammad Mahdi Industrial Engineering Department - Faculty of Engineering - Babol Noshirvani University of Technology, Babol, Iran , Safaei, Abdul Sattar Industrial Engineering Department - Faculty of Engineering - Babol Noshirvani University of Technology, Babol, Iran
Pages :
14
From page :
164
To page :
177
Abstract :
Supplier selection, order allocation and production planning are important and challenging decisions in supply chain management. There are many studies on mentioned topics separately. In this paper, a multi-objective mathematical model is proposed to optimize a sustainable supplier selection problem with order allocation and production planning simultaneously. This study considers a multi-supplier, multi-product, multi-item and multi-period supply chain. The designed mathematical model seeks to maximize total profit and minimize unsatisfied demand and total risk along with enforcing sustainability criteria in selecting suppliers. Supplier selection is a virtual process in every manufacturing company. On the other hand, this research considers all the important aspects of this problem. Therefore, the proposed framework can be implemented in many different companies like electronic, food, chemical industry. The proposed model is solved utilizing two metaheuristic algorithms including NSGA II and MOPSO. Moreover, algorithms are tuned utilizing Taguchi analysis. Furthermore, ten sample problems are generated and results are compared to identify the best algorithm for the proposed model.
Keywords :
E-commerce , Dual-channel supply chain , Joint Economic lot size , Integrated production-inventory model
Journal title :
International Journal of Supply and Operations Management (IJSOM)
Serial Year :
2020
Record number :
2509277
Link To Document :
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