مقالههای Emad Roghanian
توجه: محتویات این صفحه به صورت خودکار پردازش شده و مقالههای نویسندگانی با تشابه اسمی، همگی در بخش یکسان نمایش داده میشوند.
۱A Bi–objective Pre–emption Multi–mode Resource Constrained Project Scheduling Problem with due Dates in the Activities
اطلاعات انتشار: Journal of Optimization in Industrial Engineering، هفتم،شماره۱۵، ۲۰۱۴، سال ۰
تعداد صفحات: ۱۱
In this paper, a novel mathematical model for a preemption multi–mode multi–objective resource–constrained project scheduling problem with distinct due dates and positive and negative cash flows is presented. Although optimization of bi–objective problems with due dates is an essential feature of real projects, little effort has been made in studying the P–MMRCPSP while due dates are included in the activities. This paper tries to bridge this gap by studying tardiness MMRCPSP, in which the objective is to minimize total weighted tardiness and to maximize the net present value (NPV). In order to solve the given problem, we introduced a Non–dominated Ranking Genetic Algorithm (NRGA) and Non–Dominated Sort Genetic Algorithm (NSGA–II). Since the effectiveness of most meta–heuristic algorithms significantly depends on choosing the proper parameters. A Taguchi experimental design method was applied to set and estimate the proper values of GAs parameters for improving their performances. To prove the efficiency of our proposed meta–heuristic algorithms, a number of test problems taken from the project scheduling problem library (PSPLIB) were solved. The computational results show that the proposed NSGA–II outperforms the NRGA.
اطلاعات انتشار: Scientia Iranica، بيست و دوم،شماره۳، ۲۰۱۵، سال ۰
تعداد صفحات: ۱۳
Recently two important methods (,) [Wang. Zh.X, Liu. Y.J, and Feng. B, “Ranking L–R fuzzy number based on deviation degree”. information science(2009). pp 2070–2077.],and [Wang.Y.M, and Luo. Y, “Area ranking of fuzzy numbers based on positive and negative ideal points.’’ Computers and Mathematics with Applications(2009). pp 1769–1779.] proposed for ranking fuzzy numbers. But we found that they both have a same basic disadvantage. In this paper after a short review on different proposed fuzzy number ranking methods, we explain the drawback on deviation degree and the area ranking methods and provide an improvement method to overcome this shortage. Our approach is based on the maximization set and minimization set methods concepts. The results show the superiority of the proposed method in comparison with other ranking methods, especially when the ranking of the inverse and the symmetry of the fuzzy numbers is of interest.
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