@inproceedings{scholars119,
             doi = {10.1109/ICSMC.2006.384595},
            note = {cited By 18; Conference of 2006 IEEE International Conference on Systems, Man and Cybernetics ; Conference Date: 8 October 2006 Through 11 October 2006; Conference Code:70120},
          volume = {4},
         address = {Taipei},
           title = {A multi-objective evolutionary approach for fuzzy optimization in production planning},
            year = {2006},
           pages = {3120--3125},
       publisher = {Institute of Electrical and Electronics Engineers Inc.},
         journal = {Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics},
        abstract = {This paper outlines, first, a real-world industrial problem for product-mix selection involving 8 variables and 21 constraints with fuzzy coefficients and thereafter, a multi-objective optimization approach to solve the problem. This problem occurs in production planning in which a decision-maker plays a pivotal role in making decision under fuzzy environment. Decision-maker should be aware of his/her level-of-satisfaction as well as degree of fuzziness while making the product-mix decision. Thus, the authors have analyzed using a modified S-curve membership function the fuzziness patterns and fuzzy sensitivity of the solution found from the multi-objective optimization methodology. An ad hoc Pareto-based multi-objective evolutionary algorithm is proposed to capture multiple non dominated solutions in a single run of the algorithm. Results obtained have been compared with the well-known multi-objective evolutionary algorithm NSGA-II. {\^A}{\copyright} 2006 IEEE.},
             url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-34548125785&doi=10.1109\%2fICSMC.2006.384595&partnerID=40&md5=ef869c3dd11f03eababb591c81716c55},
        keywords = {Decision making; Evolutionary algorithms; Fuzzy sets; Sensitivity analysis, Multiple non dominated solutions; Product mix decision; Production planning, Multi agent systems},
            isbn = {1424401003; 9781424401000},
          author = {Jim{\~A}{\copyright}nez, F. and S{\~A}!nchez, G. and Vasant, P. and Verdegay, J. L.},
            issn = {1062922X}
}