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Approximation Methods for Solving the Equitable Location Problem with Probabilistic Customer Behavior

عنوان مقاله: Approximation Methods for Solving the Equitable Location Problem with Probabilistic Customer Behavior
شناسه ملی مقاله: JR_IJIEPR-24-3_006
منتشر شده در شماره 3 دوره 24 فصل در سال 1392
مشخصات نویسندگان مقاله:

J. Bagherinejad - Assistant Professor of Industrial Engineering, Faculty of Engineering and Technology, University of Alzahra, Tehran, Iran.
M. Omidbakhsh - MSc of Industrial Engineering, Faculty of Engineering and Technology, University of Alzahra, Vanak, Tehran, Iran

خلاصه مقاله:
Location-allocation of facilities in service systems is an essential factor of their performance. One of the considerable situations which less addressed in the relevant literature is to balance service among customers in addition to minimize location-allocation costs. This is an important issue, especially in the public sector. Reviewing the recent researches in this field shows that most of them allocated demand customer to the closest facility. While, using probability rules to predict customer behavior when they select the desired facility is more appropriate. In this research, equitable facility location problem based on the gravity rule was investigated. The objective function has been defined as a combination of balancing and cost minimization, keeping in mind some system constraints. To estimate demand volume among facilities, utility function(attraction function) added to model as one constraint. The research problem is modeled as one mixed integer linear programming. Due to the model complexity, two heuristic and genetic algorithms have been developed and compared by exact solutions of small dimension problems. The results of numerical examples show the heuristic approach effectiveness with good-quality solutions in reasonable run time.

کلمات کلیدی:
Facility location; Equitable load; Gravity model; Heuristic algorithm; Genetic algorithm; Integer programming

صفحه اختصاصی مقاله و دریافت فایل کامل: https://civilica.com/doc/281430/