{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/fish-school-search-algorithm-for-constrained","title":"Fish School Search Algorithm for Constrained Optimization","arxiv_id":"1707.06169","date":"2017-07-19","proceeding":null,"authors":["Joao Batista Monteiro Filho","Isabela Maria Carneiro de Albuquerque","Fernando Buarque de Lima Neto"],"abstract":"In this work we investigate the effectiveness of the application of niching\nable swarm metaheuristic approaches in order to solve constrained optimization\nproblems. Sub-swarms are used in order to allow the achievement of many\nfeasible regions to be exploited in terms of fitness function. The niching\napproach employed was wFSS, a version of the Fish School Search algorithm\ndevised specifically to deal with multi-modal search spaces. A base technique\nreferred as wrFSS was conceived and three variations applying different\nconstraint handling procedures were also proposed. Tests were performed in\nseven problems from CEC 2010 and a comparison with other approaches was carried\nout. Results show that the search strategy proposed is able to handle some\nheavily constrained problems and achieve results comparable to the\nstate-of-the-art algorithms. However, we also observed that the local search\noperator present in wFSS and inherited by wrFSS makes the fitness convergence\ndifficult when the feasible region presents some specific geometrical features.","url_abs":"http://arxiv.org/abs/1707.06169v1","url_pdf":"http://arxiv.org/pdf/1707.06169v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"fish-school-search-algorithm-for-constrained","repo_url":"https://github.com/nafiuny/AFSA-algorithm","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}