{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,2]],"date-time":"2026-05-02T06:10:53Z","timestamp":1777702253996,"version":"3.51.4"},"reference-count":0,"publisher":"SAGE Publications","issue":"5","license":[{"start":{"date-parts":[[2012,1,1]],"date-time":"2012-01-01T00:00:00Z","timestamp":1325376000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Journal of Intelligent &amp; Fuzzy Systems"],"published-print":{"date-parts":[[2012,8]]},"abstract":"<jats:p>In this paper, we present a new Multi-Agent System for reduction of the bullwhip effect in fuzzy supply chains. First, we show that a supply chain that uses an optimal ordering policy without data sharing among echelons still suffers from the bullwhip effect. Then, we propose the multi-agent solution to manage and reduce the bullwhip effect. The proposed multi-agent system includes four different types of agents in which each agent has its own list of actions. The proposed Multi-agent System applies a new Tabu Search algorithm for fuzzy rule generation, and a new data filtering algorithm for extraction of the bullwhip-free data from supply chain data warehouse. We validate the multi-agent system under different conditions and discuss how the system responds to different factors. The results show that the proposed multi-agent system reduces the bullwhip effect significantly in a rational time.<\/jats:p>","DOI":"10.3233\/ifs-2012-0517","type":"journal-article","created":{"date-parts":[[2019,12,2]],"date-time":"2019-12-02T17:42:18Z","timestamp":1575308538000},"page":"259-268","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":4,"title":["A multi-agent solution for reduction of bullwhip effect in fuzzy supply chains"],"prefix":"10.1177","volume":"23","author":[{"given":"M.H. Fazel","family":"Zarandi","sequence":"first","affiliation":[{"name":"Department of Industrial Engineering, Amirkabir University of Technology, Tehran, Iran"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"M.","family":"Avazbeigi","sequence":"additional","affiliation":[{"name":"Collaborative Intelligent Systems Laboratory, European Centre for Soft Computing, Mieres, Asturias, Spain"},{"name":"Intelligent Signal Processing Group, Department of Electronics, University of Barcelona, Barcelona, Spain"},{"name":"Artificial Olfaction Group, Institute for Bioengineering of Catalonia, Barcelona, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","published-online":{"date-parts":[[2012,1]]},"container-title":["Journal of Intelligent &amp; Fuzzy Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.3233\/IFS-2012-0517","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.3233\/IFS-2012-0517","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,29]],"date-time":"2026-04-29T09:35:20Z","timestamp":1777455320000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.sagepub.com\/doi\/10.3233\/IFS-2012-0517"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2012,1]]},"references-count":0,"journal-issue":{"issue":"5","published-print":{"date-parts":[[2012,8]]}},"alternative-id":["10.3233\/IFS-2012-0517"],"URL":"https:\/\/doi.org\/10.3233\/ifs-2012-0517","relation":{},"ISSN":["1064-1246","1875-8967"],"issn-type":[{"value":"1064-1246","type":"print"},{"value":"1875-8967","type":"electronic"}],"subject":[],"published":{"date-parts":[[2012,1]]}}}