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Journal of Artificial Intelligence and Data Mining، جلد ۹، شماره ۴، صفحات ۴۹۷-۵۱۴
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عنوان انگلیسی A Multi-objective Approach based on Competitive Optimization Algorithm and its Engineering Applications
چکیده انگلیسی مقاله A new multi-objective evolutionary optimization algorithm is presented based on the competitive optimization algorithm (COOA) to solve multi-objective optimization problems (MOPs). Based on nature-inspired competition, the competitive optimization algorithm acts between animals such as birds, cats, bees, ants, etc. The present study entails main contributions as follows: First, a novel method is presented to prune the external archive and at the same time keep the diversity of the Pareto front (PF). Second, a hybrid approach of powerful mechanisms such as opposition-based learning and chaotic maps is used to maintain the diversity in the search space of the initial population. Third, a novel method is provided to transform a multi-objective optimization problem into a single-objective optimization problem. A comparison of the result of the simulation for the proposed algorithm was made with some well-known optimization algorithms. The comparisons show that the proposed approach can be a better candidate to solve MOPs.
کلیدواژه‌های انگلیسی مقاله Multi-objective optimization, Competitive optimization algorithm, Initial population, Engineering design problems, Proposed crowding distance
نویسندگان مقاله Y. Sharafi |
Department of Computer Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran

M. Teshnelab |
Intelligent Systems Laboratory, Faculty of Electrical and Computer Engineering, K. N. Toosi University of Technology, Tehran, Iran.

M. Ahmadieh Khanesar |
Faculty of Engineering, University of Nottingham, Nottingham, UK.

نشانی اینترنتی http://jad.shahroodut.ac.ir/article_2145_9b3c4ea01f6cfec5c1259f65fa0812eb.pdf
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