| Experimental Comparison of GA/NSGA-II Operator and Encoding Choices in MATLAB: A Reproducible Two-Variable Non-Convex Benchmark |
| کد مقاله : 1560-ISME2026 |
| نویسندگان |
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نگین سادات حسینی نوید *1، محمد مهدی سلطانی2 1پژوهشگر
دانشجوی دانشگاه علم وصنعت ایران 2پژوهشگر به آدرس: مجیدیه شمالی - خ.برادران محمدی(ریحانی)-خیابان صباح شرقی-بلوار توکل-خیابان افتخار شرقی مجتمع بام سامان- واحد 721 |
| چکیده مقاله |
| This paper presents an instructional and reproducible assessment of how operator choice and encoding affect GA/NSGA-II performance on a non-convex, oscillatory two-variable benchmark over x,y∈[-10,10]. A real-coded GA (MATLAB ga) was tested under six crossover–mutation pairings (single-point, two-point, arithmetic) × (uniform, Gaussian), with 20 independent runs per pairing; best objective value, associated (x,y), and runtime were recorded. A binary GA with a 32-bit chromosome (16 bits per variable) and linear decoding to [−10,10] was then compared against the best real-coded setting (arithmetic + Gaussian), reaching the same reported best minimum f(x,y)≈-21.056905. Finally, a multiobjective variant was solved using MATLAB gamultiobj (NSGA-II) by defining the second objective as the inverse of the first; nine operator combinations (3 crossovers × 3 mutations) were evaluated and Pareto fronts were analyzed in terms of coverage and diversity. |
| کلیدواژه ها |
| Genetic Algorithm; NSGA-II; operator comparison; binary encoding; MATLAB |
| وضعیت: پذیرفته شده برای ارائه شفاهی |