A λ-cut and goal-programming-based algorithm for fuzzy-linear multiple-objective bilevel optimization

39Citations
Citations of this article
11Readers
Mendeley users who have this article in their library.
Get full text

Abstract

Bilevel-programming techniques are developed to handle decentralized problems with two-level decision makers, which are leaders and followers, who may have more than one objective to achieve. This paper proposes a λ-cut and goal-programming-based algorithm to solve fuzzy-linear multiple-objective bilevel (FLMOB) decision problems. First, based on the definition of a distance measure between two fuzzy vectors using λ-cut, a fuzzy-linear bilevel goal (FLBG) model is formatted, and related theorems are proved. Then, using a λ-cut for fuzzy coefficients and a goal-programming strategy for multiple objectives, a λ-cut and goal-programming-based algorithm to solve FLMOB decision problems is presented. A case study for a newsboy problem is adopted to illustrate the application and executing procedure of this algorithm. Finally, experiments are carried out to discuss and analyze the performance of this algorithm. © 2006 IEEE.

Cite

CITATION STYLE

APA

Gao, Y., Zhang, G., Ma, J., & Lu, J. (2010). A λ-cut and goal-programming-based algorithm for fuzzy-linear multiple-objective bilevel optimization. IEEE Transactions on Fuzzy Systems, 18(1), 1–13. https://doi.org/10.1109/TFUZZ.2009.2030329

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free