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RESOLUTION OF NONLINEAR OPTIMIZATION PROBLEMS SUBJECT TO BIPOLAR MAX-MIN FUZZY RELATION EQUATION CONSTRAINTS USING GENETIC ALGORITHM | ||
| Iranian Journal of Fuzzy Systems | ||
| مقالات آماده انتشار، پذیرفته شده ، انتشار آنلاین از تاریخ 11 تیر 1396 | ||
| نوع مقاله: Research Paper | ||
| شناسه دیجیتال (DOI): 10.22111/ijfs.2017.3290 | ||
| نویسندگان | ||
Hassan Dana Mazraeh؛ Ali Abbasi Molai 
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| School of Mathematics and Computer Sciences, Damghan University, Damghan, Iran | ||
| چکیده | ||
| This paper studies the nonlinear optimization problems subject to bipolar max-min fuzzy relation equation constraints. The feasible solution set of the problems is non-convex, in a general case. Therefore, conventional nonlinear optimization methods cannot be ideal for resolution of such problems. Hence, a Genetic Algorithm (GA) is proposed to find their optimal solution. This algorithm uses the structure of the feasible domain of the problems and lower and upper bound of the feasible solution set to choose the initial population. The GA employs two different crossover operations: 1- N-points crossover and 2- Arithmetic crossover. We run the GA with two crossover operations for some test problems and compare their results and performance to each other. Also, their results are compared with the results of other authors' works. | ||
| کلیدواژه ها | ||
| Bipolar fuzzy relation equations؛ Max-min composition؛ Nonlinear optimization؛ Genetic Algorithm | ||
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آمار تعداد مشاهده مقاله: 127 |
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