%0 Journal Article %T A Multi-objective Approach based on Competitive Optimization Algorithm and its Engineering Applications %J Journal of AI and Data Mining %I Shahrood University of Technology %Z 2322-5211 %A Sharafi, Y. %A Teshnelab, M. %A Ahmadieh Khanesar, M. %D 2021 %\ 11/01/2021 %V 9 %N 4 %P 497-514 %! A Multi-objective Approach based on Competitive Optimization Algorithm and its Engineering Applications %K Multi-objective optimization %K Competitive optimization algorithm %K Initial population %K Engineering design problems %K Proposed crowding distance %R 10.22044/jadm.2021.10698.2204 %X 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. %U https://jad.shahroodut.ac.ir/article_2145_9b3c4ea01f6cfec5c1259f65fa0812eb.pdf