Bounded Primal Simplex Algorithm for Bounded Linear Programming with Fuzzy Cost Coefficients

Ali Ebrahimnejad, Seyed Hadi Nasseri and Sayyed Mehdi Mansourzadeh
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Ali Ebrahimnejad: Islamic Azad University, Qaemshahr Branch, Iran
Seyed Hadi Nasseri: Mazandaran University, Iran
Sayyed Mehdi Mansourzadeh: Islamic Azad University, Jouybar Branch, Iran

International Journal of Operations Research and Information Systems (IJORIS), 2011, vol. 2, issue 1, 96-120

Abstract: In most practical problems of linear programming problems with fuzzy cost coefficients, some or all variables are restricted to lie within lower and upper bounds. In this paper, the authors propose a new method for solving such problems called the bounded fuzzy primal simplex algorithm. Some researchers used the linear programming problem with fuzzy cost coefficients as an auxiliary problem for solving linear programming with fuzzy variables, but their method is not efficient when the decision variables are bounded variables in the auxiliary problem. In this paper the authors introduce an efficient approach to overcome this shortcoming. The bounded fuzzy primal simplex algorithm starts with a primal feasible basis and moves towards attaining primal optimality while maintaining primal feasibility throughout. This algorithm will be useful for sensitivity analysis using primal simplex tableaus.

Date: 2011
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