IJE TRANSACTIONS A: Basics Vol. 31, No. 7 (July 2018) 1066-1073    Article in Press

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M. Ebrahimi, R. Tavakkoli-Moghaddam and F. Jolai
( Received: September 18, 2017 – Accepted in Revised Form: January 04, 2018 )

Abstract    Taking into account competitive markets, manufacturers attend more customerís personalization. Accordingly, build-to-order systems have been given more attention in recent years. In these systems, the customer is a very important asset for us and has been paid less attention in the previous studies. This paper introduces a new build-to-order problem in the supply chain. This study focuses on both manufacturer's profit and customer's utility simultaneously where demand is dependent on customer's utility. The customer's utility is a behavior based upon utility function that depends on quality and price and customer's preferences. The new bi-objective non-linear problem is a multi-period, multi-product and three-echelon supply chain in order to increase manufacturer's profit and customer's utility simultaneously. Solving the complicated problem, two multi-objective meta-heuristics, namely non-dominated ranked genetic algorithm (NRGA) and non-dominated sorting genetic algorithm (NSGA-II), were used to solve the given problem. Finally, the outcomes obtained by these meta-heuristics are analyzed.


Keywords    Build-to-order; Bi-objective Model; Supply Chain; Customer Utility; Multi-objective meta-heuristics


چکیده    با توجه به بازار رقابتی، تولیدکنندگان بیشتر به سفارشی سازی روی آورده≠اند. از اینرو، سیستم≠های ساخت بر اساس سفارش بیشتر مورد توجه قرار گرفته≠اند. از آنجایی که در این سیستم≠ها، مشتری جایگاه ویژه≠ای دارد و در مطالعات گذشته کمتر به آن توجه شده است. در این مقاله، یک مدل جدید زنجیره تامین ساخت بر اساس سفارش بررسی می≠شود که به طور همزمان به بهینه سازی سیستم≠های ساخت بر اساس سفارش از دو منظر مطلوبیت مشتری و سود تولیدکننده می≠پردازد به طوری که تقاضا وابسته به مطلوبیت مشتری است و مطلوبیت مشتری تابعی از قیمت، کیفیت و ترجیحات مشتری می≠باشد. مدل جدید غیرخطی دو هدفه ارائه شده، چند دوره≠ای، چندمحصولی و چندسطحی با هدف افزایش سود تولیدکننده و مطلوبیت مشتری به طور همزمان است که با استفاده از دو روش فرابتکاری الگوریتم ژنتیک رتبه بندی غیرمغلوب و الگوریتم ژنتیک مرتب سازی غیرمغلوب حل می≠شوند. در پایان نتایج مورد تحلیل قرار می≠گیرند.


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