Rahimi, Iman, Hong Tang, Sai, Ahmadi, Abdollah, Binti Ahmad, Siti Azfanizam, Lee, Lai Soon, M. Sharaf, Adel. (1396). Evaluating the Effectiveness of Integrated Benders Decomposition Algorithm and Epsilon Constraint Method for Multi-Objective Facility Location Problem under Demand Uncertainty. , 10(3), 551-576. doi: 10.22059/ijms.2017.229298.672575
Iman Rahimi; Sai Hong Tang; Abdollah Ahmadi; Siti Azfanizam Binti Ahmad; Lai Soon Lee; Adel M. Sharaf. "Evaluating the Effectiveness of Integrated Benders Decomposition Algorithm and Epsilon Constraint Method for Multi-Objective Facility Location Problem under Demand Uncertainty". , 10, 3, 1396, 551-576. doi: 10.22059/ijms.2017.229298.672575
Rahimi, Iman, Hong Tang, Sai, Ahmadi, Abdollah, Binti Ahmad, Siti Azfanizam, Lee, Lai Soon, M. Sharaf, Adel. (1396). 'Evaluating the Effectiveness of Integrated Benders Decomposition Algorithm and Epsilon Constraint Method for Multi-Objective Facility Location Problem under Demand Uncertainty', , 10(3), pp. 551-576. doi: 10.22059/ijms.2017.229298.672575
Rahimi, Iman, Hong Tang, Sai, Ahmadi, Abdollah, Binti Ahmad, Siti Azfanizam, Lee, Lai Soon, M. Sharaf, Adel. Evaluating the Effectiveness of Integrated Benders Decomposition Algorithm and Epsilon Constraint Method for Multi-Objective Facility Location Problem under Demand Uncertainty. , 1396; 10(3): 551-576. doi: 10.22059/ijms.2017.229298.672575

Evaluating the Effectiveness of Integrated Benders Decomposition Algorithm and Epsilon Constraint Method for Multi-Objective Facility Location Problem under Demand Uncertainty

Interdisciplinary Journal of Management Studies
مقاله 1، دوره 10، شماره 3، 2017، صفحه 551-576    اصل مقاله (861.53 K)
نوع مقاله: Research Paper
شناسه دیجیتال (DOI): 10.22059/ijms.2017.229298.672575
نویسندگان
Iman Rahimi* 1؛ Sai Hong Tang1؛ Abdollah Ahmadi2؛ Siti Azfanizam Binti Ahmad1؛ Lai Soon Lee3؛ Adel M. Sharaf4
1Department of Mechanical and Manufacturing Engineering, Faculty of Engineering, University Putra Malaysia, Malaysia
2Australian Energy Research Institute and the School of Electrical Engineering and Telecommunications, University of New South Wales, Sydney, NSW 2032, Australia
3Department of Mathematics, Faculty of Science, 43400 UPM Serdang, Selangor Malaysia,
4Department of Electrical and Computer Engineering, University of New Brunswick, P.O. Box 4400-UNB, Fredericton, NB, Canada E3B 5A3
چکیده
One of the most challenging issues in multi-objective problems is finding Pareto optimal points. This paper describes an algorithm based on Benders Decomposition Algorithm (BDA) which tries to find Pareto solutions. For this aim, a multi-objective facility location allocation model is proposed. In this case, an integrated BDA and epsilon constraint method are proposed and it is shown that how Pareto points in multi-objective facility location model can be found. Results are compared with the classic form of BDA and the weighted sum method for demand uncertainty and deterministic demands. To do this, Monte Carlo method with uniform function is used, then the stability of the proposed method towards demand uncertainty is shown. In order to evaluate the proposed algorithm, some performance metrics including the number of Pareto points, mean ideal points, and maximum spread are used, then the t-test analysis is done which points out that there is a significant difference between aforementioned algorithms.
کلیدواژه‌ها
Benders decomposition algorithm؛ demand uncertainty؛ multi-objective optimisation
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آمار
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