RT - Journal Article T1 - Providing a Multi-Objective Optimization Algorithm Based on Probabilistic Crossover and Bi-Directional Mutation for Solving I-Beam Designing Problem JF - JAMLU YR - 2020 JO - JAMLU VO - 17 IS - 3 UR - http://jamlu.liau.ac.ir/article-1-1645-en.html SP - 119 EP - 133 K1 - Multi-Objective Optimization K1 - I-Beam Designing K1 - Probabilistic Crossover K1 - Bi-Directional Mutation AB - Today, multi-objective optimization algorithms are used as powerful tools for solving several problems. In any multi-objective optimization algorithm, diversity and convergence are two of the most important factors that need to be improved. Diversity and convergence are functions of exploration, exploitation, and selection operators. Effective algorithms should be used by different operators to achieve a robust optimization algorithm. In this study, a multi-objective optimization algorithm is proposed to enhance the diversity and convergence for solving the I-beam engineering problem. The proposed algorithm uses a proposed bi-directional mutation algorithm to exploit search space and uses the proposed probabilistic crossover algorithm to explore the search space. In this study, the hyper volume metric has been used to evaluate convergence and diversity. In the final section of this study, the overall performance of the proposed algorithm is compared with algorithms such as SPEA, NSGAII, NSPSO, and AWPSO in order to solve the I-beam designing problem. The results obtained from multi-objective optimization algorithms for solving I-beam designing problem indicate the superiority of the proposed algorithm in comparison to other known algorithms. LA eng UL http://jamlu.liau.ac.ir/article-1-1645-en.html M3 ER -