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International Journal of Machine Learning and Cybernetics
Erschienen in: International Journal of Machine Learning and Cybernetics 6/2013

01.12.2013 | Original Article

A fuzzy approach to multicriteria assignment problem using exponential membership functions

verfasst von: Pankaj Gupta, Mukesh K. Mehlawat, Garima Mittal

Erschienen in: International Journal of Machine Learning and Cybernetics | Ausgabe 6/2013

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Abstract

In this paper, we extend the classical assignment problem to the multicriteria assignment problem by considering three criteria: cost, time and quality subject to many realistic constraints including multi-job assignment and a knapsack-type resource constraint. The paper addresses the uncertainty of the real-life assignment problem by formulating a fuzzy cost–time–quality assignment problem using exponential membership functions. We define fuzzy goal for each criterion as per the preferences of the decision-maker and aggregate the fuzzy goals using product operator. In order to obtain optimal assignment plans, the resultant nonlinear 0-1 optimization problem is solved using genetic algorithm for different choices of the shape parameters in the exponential membership functions. As an illustrative example, we consider a fuzzy manpower planning problem.
Vorheriger Artikel Fuzzy rough set models over two universes
Nächster Artikel Intuitionistic fuzzy filter theory of BL-algebras

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Metadaten
Titel
A fuzzy approach to multicriteria assignment problem using exponential membership functions
verfasst von
Pankaj Gupta
Mukesh K. Mehlawat
Garima Mittal
Publikationsdatum
01.12.2013
Verlag
Springer Berlin Heidelberg
Erschienen in
International Journal of Machine Learning and Cybernetics / Ausgabe 6/2013
Print ISSN: 1868-8071
Elektronische ISSN: 1868-808X
DOI
https://doi.org/10.1007/s13042-012-0122-8

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