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Multilevel Programming Problems with Fuzzy Parameters: A Fuzzy Goal Programming Approach

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International Journal of Computer Applications
© 2015 by IJCA Journal
Volume 122 - Number 21
Year of Publication: 2015
Authors:
Surapati Pramanik
10.5120/21852-5174

Surapati Pramanik. Article: Multilevel Programming Problems with Fuzzy Parameters: A Fuzzy Goal Programming Approach. International Journal of Computer Applications 122(21):34-41, July 2015. Full text available. BibTeX

@article{key:article,
	author = {Surapati Pramanik},
	title = {Article: Multilevel Programming Problems with Fuzzy Parameters: A Fuzzy Goal Programming Approach},
	journal = {International Journal of Computer Applications},
	year = {2015},
	volume = {122},
	number = {21},
	pages = {34-41},
	month = {July},
	note = {Full text available}
}

Abstract

This paper presents fuzzy goal programming approach for solving multilevel programming problems with fuzzy parameters. The proposed approach is based on ? -cut and fuzzy goal programming. In the proposed approach, the tolerance membership functions for the fuzzily described objective functions are defined by determining individual best solution of the objective function of every decision maker. Since the objectives of the level decision makers are potentially conflicting in nature, decision deadlock may arise due to the dissatisfaction of the solution of upper level decision makers. Sometimes upper level decision makers insist to work more than stipulated working hours or overtime duty in order to meet the heavy demand of the market arising for festivals or emergency reasons. In order to survive in the open competitive market, the relaxations of lower level decision makers are very crucial for the upper level decision makers and for the organization. So in the proposed model relaxation of decision for each level decision maker is considered. The relaxation of decision is performed by providing preference bounds on the decision variables for avoiding decision deadlock. Then three fuzzy goal programming models for multilevel programming are formulated. In general, the fuzzy goal programming models offer different solutions. In order to find the best compromise solution Euclidean function is used. An illustrative numerical example is provided to demonstrate the efficiency of the proposed approach.

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