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

被引：46

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

页码：1 / 13

页数：13

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