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We then used the expected value operator and the chance-constrained operator to handle the random fuzzy objective functions and the random fuzzy constraints. The solution scheme was pursued by a genetic algorithm based on random fuzzy simulation and compromise approach. And an application to a Chinese beer company was given as an illustration. <\/jats:p>","DOI":"10.1142\/s0218488509006285","type":"journal-article","created":{"date-parts":[[2009,11,30]],"date-time":"2009-11-30T01:55:56Z","timestamp":1259546156000},"page":"807-831","source":"Crossref","is-referenced-by-count":6,"title":["A CLASS OF INTEGRATED LOGISTICS NETWORK MODEL UNDER RANDOM FUZZY ENVIRONMENT AND ITS APPLICATION TO CHINESE BEER COMPANY"],"prefix":"10.1142","volume":"17","author":[{"given":"XIAOYANG","family":"ZHOU","sequence":"first","affiliation":[{"name":"Uncertainty Decision-Making Laboratory, Sichuan University, Chengdu 610064, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"JIUPING","family":"XU","sequence":"additional","affiliation":[{"name":"Uncertainty Decision-Making Laboratory, Sichuan University, Chengdu 610064, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"219","published-online":{"date-parts":[[2011,11,21]]},"reference":[{"key":"rf1","volume-title":"Reverse Logistics","author":"Stock J. 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