Applying modified NSGA-II for bi-objective supply chain problem

• Published in: Journal of intelligent manufacturing Vol. 24; no. 4; pp. 707 - 716
• Main Authors: Bandyopadhyay, Susmita, Bhattacharya, Ranjan
• Format: Journal Article
• Language: English
• Published: Boston Springer US 01-08-2013; Springer Nature B.V
• Subjects: Algorithms; Analysis; Business and Management; Control; Elitism; Fuzzy logic; Genetic algorithms; Machines; Manufacturing; Mechatronics; Mutation; Optimization; Order quantity; Processes; Production; Robotics; Studies; Supply chains; Wholesalers; Supply chain; NSGA-II; Mutation; Fuzzy order; Crossover
• ISSN: 0956-5515; 1572-8145
• DOI: 10.1007/s10845-011-0617-2

This paper minimizes the value of total cost and bullwhip effect in a supply chain. The objectives have been achieved through developing a new multi-objective formulation for minimizing the total cost and minimizing the bullwhip effect of a two-echelon serial supply chain. A new crossover algorithm for a fuzzy variable and a new mutation algorithm have also been proposed while applying Non-dominated Sorting Genetic Algorithm-II (NSGA-II) to the proposed problem. The formulated problem has been simulated by Matlab software and the results of the modified NSGA-II have been compared with those of original NSGA-II. It is found from the results that the modified NSGA-II algorithm performs better than the original NSGA-II algorithm since the minimum values for both total cost and the bullwhip effect are obtained in case of the modified NSGA-II. The formulated bi-objective problem is new to the research community. The minimization of bullwhip effect has never been considered in a multi-objective optimization before. Besides crossover operator applied to the fuzzy variable and the mutation operator are newly introduced operators.