Compromise Fuzzy Multi-Objective Linear Programming (CFMOLP) heuristic for product-mix determination

► This paper models a crisp Linear Programming (LP) as a Compromise Fuzzy Multi-Objective LP (CFMOLP). ► The application of CFMOLP has been focused on an industrial engineering problem that seeks profit maximisation by optimising product-mix. ► Imprecision of the large volume of industrial data and...

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Vydané v:Computers & industrial engineering Ročník 61; číslo 3; s. 582 - 590
Hlavní autori: Susanto, Sani, Bhattacharya, Arijit
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: New York Elsevier Ltd 01.10.2011
Pergamon Press Inc
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ISSN:0360-8352, 1879-0550
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Shrnutí:► This paper models a crisp Linear Programming (LP) as a Compromise Fuzzy Multi-Objective LP (CFMOLP). ► The application of CFMOLP has been focused on an industrial engineering problem that seeks profit maximisation by optimising product-mix. ► Imprecision of the large volume of industrial data and the conglomerated decision from all levels of management lead fuzzication of the identified constraints and the objective functions as well. ► The crisp model described is in the form of crisp-Multi-Objective Linear Programming (MOLP) with objective functions, functional constraints and non-negativity constraints. ► This model is formulated as a fuzzy-MOLP and subsequently converted into an equivalent compromise-MOLP model. ► The paper describes the development process for the CFMOLP model and its application along with appropriate interpretation. This paper models a crisp Linear Programming (LP) as a Compromise Fuzzy Multi-Objective LP (CFMOLP). The application of CFMOLP has been focused on an industrial engineering problem that seeks profit maximisation by optimising product-mix. Imprecision of the large volume of industrial data and the conglomerated decision from all levels of management lead fuzzication of the identified constraints and the objective functions as well. The crisp model described is in the form of crisp-Multi-Objective Linear Programming (MOLP) with objective functions, functional constraints and non-negativity constraints. This model is formulated as a fuzzy-MOLP and subsequently converted into an equivalent compromise-MOLP model. The paper describes the development process for the CFMOLP model and its application along with appropriate interpretation.
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ISSN:0360-8352
1879-0550
DOI:10.1016/j.cie.2011.04.013