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Article type: Research Article
Authors: Boroushaki, Mehrdad | Ghofrani, Mohammad B. | Lucas, Caro
Affiliations: Department of Mechanical Engineering, Sharif University of Technology, P.O. Box 11365-9567, Tehran, Iran | Department of Electrical and Computer Engineering, Tehran University, P.O. Box 14395-515, Tehran, Iran
Note: [] Corresponding author. Tel.: +98 913 206 3587; Fax: +98 21 6013128; E-mail: [email protected]
Abstract: In pressurized water reactors, the fuel reloading problem has significant meaning in terms of both safety and economics. An optimal loading pattern is defined as a pattern in which the local power peaking factor (P_q) is lower than a predetermined value during one cycle and the effective multiplication factor (k_{eff}) is maximized to extract the maximum energy. This article presents a specialized genetic algorithm for loading pattern design. The tests on well-researched cases have shown that the genetic algorithm is capable of finding better loading patterns than solutions found by direct search methods. However, most of the previous researchers have considered simple fitness (cost) functions; therefore the reported solutions cannot minimize the P_qtogether with maximization of the k_{eff}. To solve this difficulty, we used Fuzzy Nonlinear Programming (FNLP) technique with the genetic algorithm to perform multi-objective optimization (maximizing the k_{eff}together with minimizing the P_q). The results show that this method improves the genetic algorithm results compared to previous methods.
Journal: Journal of Intelligent & Fuzzy Systems, vol. 14, no. 2, pp. 85-93, 2003
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