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

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

Ali Ebrahimnejad, Seyed Hadi Nasseri, Sayyed Mehdi Mansourzadeh
Copyright: © 2011 |Volume: 2 |Issue: 1 |Pages: 25
ISSN: 1947-9328|EISSN: 1947-9336|EISBN13: 9781613508756|DOI: 10.4018/joris.2011010105
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MLA

Ebrahimnejad, Ali, et al. "Bounded Primal Simplex Algorithm for Bounded Linear Programming with Fuzzy Cost Coefficients." IJORIS vol.2, no.1 2011: pp.96-120. http://doi.org/10.4018/joris.2011010105

APA

Ebrahimnejad, A., Nasseri, S. H., & Mansourzadeh, S. M. (2011). Bounded Primal Simplex Algorithm for Bounded Linear Programming with Fuzzy Cost Coefficients. International Journal of Operations Research and Information Systems (IJORIS), 2(1), 96-120. http://doi.org/10.4018/joris.2011010105

Chicago

Ebrahimnejad, Ali, Seyed Hadi Nasseri, and Sayyed Mehdi Mansourzadeh. "Bounded Primal Simplex Algorithm for Bounded Linear Programming with Fuzzy Cost Coefficients," International Journal of Operations Research and Information Systems (IJORIS) 2, no.1: 96-120. http://doi.org/10.4018/joris.2011010105

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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.

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