1403/01/10
سید هادی ناصری

سید هادی ناصری

مرتبه علمی: دانشیار
ارکید:
تحصیلات: دکترای تخصصی
اسکاپوس:
دانشکده: دانشکده علوم ریاضی
نشانی:
تلفن: 01135302472

مشخصات پژوهش

عنوان
A fuzzy stochastic multi-objective optimization model to configure a supply chain considering new product development
نوع پژوهش
JournalPaper
کلیدواژه‌ها
Supply chain New product development Fuzzy stochastic linear programming Revised multi-choice goal programming
سال
2016
مجله APPLIED MATHEMATICAL MODELLING
شناسه DOI
پژوهشگران Zahra Alizadeh ، Seyed Hadi Nasseri ، Iraj Mahdavi ، Mohammad Mahdi Paydar

چکیده

This study aims to design a multi-echelon, multi-objective supply chain model that incor- porates new product development and its effects on supply chain configuration. To survive in a highly competitive industry, strategies to either collaborate or compete with rival firms within a network should be considered in the new product development process, and it is crucial to pay great attention to customers’ needs and interests. Considering the imprecise nature of some critical parameters plays an important role in making suitable strategic de- cisions. This fact requires considering uncertainties of the environment such as customer demands and supplier capacities. In this study, a supply chain involving multiple suppliers, manufacturers, distributors and customers and addressing a multi-objective, multi-period and multi-product aggregate procurement and production planning problem is considered. The first objective function aims to maximize the profit of the supply chain, including that associated with new product development. The second objective function considers cus- tomer satisfaction, and the third one maximizes the production of the developed and new products. To address real-world planning problems involving noisy, incomplete or erro- neous data, the supplier capacity parameters of the supply chain and demand fluctuations are subject to uncertainty, which is modeled by fuzzy stochastic programming. Finally, the proposed multi-objective model is solved as a single-objective mixed integer programming model by applying the revised multi-choice goal programming method. In addition, a nu- merical example is provided to demonstrate the applicability of the proposed model