Efficient strict solution methods for 0-1 random fuzzy programming problems based on the necessity measure

Takashi Hasuike, Hideki Katagiri, Hiroaki Ishii

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

This paper considers two general 0-1 random fuzzy programming problems based on the degree of necessity which include some previous 0-1 stochastic and fuzzy programming problems. The proposal problems are not well defined due to including randomness and fuzziness. Therefore, by introducing chance constraint and fuzzy goal for the objective function, and considering the maximization of the aspiration level for total profit and the degree of necessity that the objective function's value satisfies the fuzzy goal, each main problem is transformed into a deterministic equivalent problem. Furthermore, by using the assumption that each random variable is distributed according to a normal distribution, the problem is equivalently transformed into a basic 0-1 programming problem, and the efficient strict solution method to find an optimal solution is constructed.

Original languageEnglish
JournalIAENG International Journal of Applied Mathematics
Volume39
Issue number2
Publication statusPublished - 2009 May
Externally publishedYes

Fingerprint

Necessity Measure
Fuzzy Programming
Normal distribution
Random variables
Profitability
Fuzzy Goals
0-1 Programming
Objective function
Chance Constraints
Stochastic Programming
Fuzziness
Randomness
Profit
Gaussian distribution
Well-defined
Optimal Solution
Random variable

Keywords

  • 0-1 programming problem
  • Degree of necessity
  • Random fuzzy variables
  • Relaxation problem

ASJC Scopus subject areas

  • Applied Mathematics

Cite this

Efficient strict solution methods for 0-1 random fuzzy programming problems based on the necessity measure. / Hasuike, Takashi; Katagiri, Hideki; Ishii, Hiroaki.

In: IAENG International Journal of Applied Mathematics, Vol. 39, No. 2, 05.2009.

Research output: Contribution to journalArticle

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