توجه: محتویات این صفحه به صورت خودکار پردازش شده و مقاله‌های نویسندگانی با تشابه اسمی، همگی در بخش یکسان نمایش داده می‌شوند.
۱A new multiobjective modeling in distribution center location problem
اطلاعات انتشار: ششمین کنفرانس بین المللی مهندسی صنایع، سال
تعداد صفحات: ۱۵
Since now, cost, distance time and other objective data have played an important role in location theory as objective functions in the location models. However they are not sufficient in facing with real world. One of the most important parameter in order to make applicable models is considering qualitative aspects which were called subjective data and they have not been considered seriously or MADM techniques were used, As decision makers opinions are one of the most effective subjective data in the location decision, it this paper we present an algorithm which is able to quantify decision markers opinions via fuzzy theory and construct a multy– objective model by inserting the quantified opinions in a basic distribution center location model. Lp–metric method is used to solve our multi–objective model. Finelly, a numerical example is expressed for illustration of the proposed method.<\div>

۲An Artificial Immune Algorithm for Minimizing Total Cost of Resources in the Resource Constrained Project Scheduling Problem
اطلاعات انتشار: نهمین کنفرانس بین المللی مهندسی صنایع، سال
تعداد صفحات: ۷
In this article, an Artificial Immune Algorithm (AIA) for minimizing total costs of both renewable and non–renewable resources in the Resource–Constrained Project Scheduling Problem (RCPSP) is presented. We assume renewable resources that are limited in number, are restricted to very expensive equipment and machines, therefore they are rented and used in other projects, and are not available in all project periods. In other words, there is a predefined ready date as well as a due date for each renewable resource type, so that no resource is used before its ready date. However, resources are permitted to be used after their due date by paying penalty costs depending on the resource type. The objective is to minimize the total costs of both renewable and non–renewable resource usages. For this purpose, we present a metaheuristic algorithm namely Artificial Immune Algorithm (AIA) inspired by the vertebrate immune system to solve this problem.In order to examine the performance of this algorithm, data derived from studied literature were used, and their answers were compared with those of the Simulated Annealing (SA) algorithm. Results show that in average, quality of AIA answers was better than those of the SA algorithm. Moreover, AIA was more sustainable.<\div>
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