A fuzzy dynamic multi-objective multi-item model by considering customer satisfaction in a supply chain

Customer satisfaction is an important issue in competitive strategic management of companies. Logistical and cross-functional drivers of supply chain have an important role in managing customer satisfaction. Customer satisfaction depends on quality, cost, and delivery. In this paper, a fuzzy mixed integer nonlinear programming model is proposed for a multi-item multi-period problem in a multi-level supply chain. Minimization of costs, manufacturing and transportation time, transportation risks, maximization of quality by minimizing the number of defective products, and maximization of customers' service levels are considered to be objective functions of the model. Furthermore, it is assumed that the demand rates are fuzzy values. An exact epsilon-constraint approach is used to solve the problem. The problem is computationally intractable. Therefore, the Non-dominant Sorting Genetic Algorithm (NSGA-II) is developed to solve it. The Taguchi method is utilized to tune the NSGA-II parameters. Finally, some numerical examples are generated and solved to evaluate the performance of the proposed model and solving methods. (C) 2017 Sharif University of Technology. All rights reserved.