A three-level optimization method for fuzzy large-scale multiobjective nonlinear programming problems

In general, mathematical models to reflect real-world complicated decision situations, are often formulated as largescale programming problems which include a large number of variables and/or constraints. Furthermore, considering the fuzziness of human's subjective judgement in real-world decis...

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Vydáno v:Fuzzy Sets and Systems Ročník 81; číslo 1; s. 141 - 155
Hlavní autoři: Yano, Hitoshi, Sakawa, Masatoshi
Médium: Journal Article
Jazyk:angličtina
japonština
Vydáno: Elsevier B.V 01.07.1996
Elsevier BV
Témata:
Add-operator
Decision making
Decomposition
Large-scale systems
Mathematical programming
Multicriteria analysis
Add-operator
Decomposition
Large-scale systems
Multicriteria analysis
Decision making
Mathematical programming
ISSN:0165-0114, 1872-6801
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Shrnutí:In general, mathematical models to reflect real-world complicated decision situations, are often formulated as largescale programming problems which include a large number of variables and/or constraints. Furthermore, considering the fuzziness of human's subjective judgement in real-world decision making, it is necessary to deal with the large-scale programming problems in the fuzzy environment. From such a point of view, in this paper, under the assumption that the decision maker (DM) has fuzzy goal for each of the objective functions and the corresponding membership function may be nonlinear, a 3-level optimization method is proposed for large-scale multiobjective nonlinear programming problems (LS-MONLPs) with the block angular structure to obtain the compromise solution of the DM. Based on the proposed algorithm, the computer program is developed in FORTRAN language, and applied to the numerical example to clarify the efficiency of the proposed algorithm.
ISSN:0165-0114
1872-6801
DOI:10.1016/0165-0114(95)00246-4