Hybrid NSGA-II for an imperfect production system considering product quality and returns under two warranty policies

作     者：Taleizadeh, Ata Allah Khaligh, Pooya Pourrezaie Moon, Ilkyeong 

作者机构：Univ Tehran Sch Ind Engn Coll Engn Tehran Iran Seoul Natl Univ Dept Ind Engn Seoul 08826 South Korea 

出 版 物：《APPLIED SOFT COMPUTING》 (应用软计算)

年 卷 期：2019年第75卷

页      面：333-348页

核心收录：

学科分类：08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：National Research Foundation of Korea (NRF) - Ministry of Science  ICT & Future Planning [2017R1A2B2007812] 

主　　题：Metaheuristics Non-dominated sorting genetic algorithm Product quality Warranty 

摘      要：This study presents a new bi-objective mathematical model for an imperfect production system (IPS) that accounts for product returns and quality levels under two different warranty policies. We considered uncertain customer demand as stochastic behavior and product price as a function of return compensation, product quality level, and warranty-period length. We simultaneously looked at the pro rata warranty and free replacement/repair warranty policies and assumed that customers can choose the desired policy. A return policy for an online distributor was also included and two objective functions were used to address the problem. The first objective function maximized the total expected revenue, and the second objective function maximized customer satisfaction. The non-dominated sorting genetic algorithm (NSGA-II) and two others, the basic bee metaheuristic and teaching-learning-based optimization algorithms, were used to generate the initial solution for use in the NSGA-II algorithm. The results from the hybrid algorithms revealed that the proposed method improves the performance of the NSGA-II algorithm. Finally, several specific sensitivity analyses were conducted to determine the effects of the problem parameters. (C) 2018 Elsevier B.V. All rights reserved.