A λ-Cut and Goal-Programming-Based Algorithm for Fuzzy-Linear Multiple-Objective Bilevel Optimization

被引：47
|
作者：
Gao, Ya [1 ]
Zhang, Guangquan [1 ]
Ma, Jun [1 ]
Lu, Jie [1 ]
机构：
[1] Univ Technol Sydney, Fac Engn & Informat Technol, Broadway, NSW 2007, Australia
来源：
IEEE TRANSACTIONS ON FUZZY SYSTEMS | 2010年 / 18卷 / 01期
基金：
澳大利亚研究理事会;
关键词：
Bilevel programming; decision making; fuzzy sets; goal programming; multiple-objective linear programming; optimization; FOLLOWER DECISION-MAKING; KUHN-TUCKER APPROACH; BOUND ALGORITHM; BRANCH; MODEL;
D O I：
10.1109/TFUZZ.2009.2030329
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
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 lambda-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.-cut, a fuzzy-linear bilevel goal (FLBG) model is formatted, and related theorems are proved. Then, using a.-cut for fuzzy coefficients and a goal-programming strategy for multiple objectives, a.-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.
引用
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页码：1 / 13
页数：13
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