A Compromise-Based Particle Swarm Optimization Algorithm for Solving Bi-Level Programming Problems with Fuzzy Parameters

Publication Type:
Conference Proceeding
Intelligent Systems and Knowledge Engineering (ISKE), 2015 10th International Conference on, 2015, pp. 214 - 221
Issue Date:
Full metadata record
Files in This Item:
Filename Description Size
ISKE-0524.pdfAccepted Manuscript569.97 kB
Adobe PDF
Bi-level programming has arisen to handle decentralized decision-making problems that feature interactive decision entities distributed throughout a bi-level hierarchy. Fuzzy parameters often appear in such a problem in applications and this is called a fuzzy bi-level programming problem. Since the existing approaches lack universality in solving such problems, this study aims to develop a particle swarm optimization (PSO) algorithm to solve fuzzy bi-level programming problems in the linear and nonlinear versions. In this paper, we first present a general fuzzy bi-level programming problem and discuss related theoretical properties based on a fuzzy number ranking method commonly used. A PSO algorithm is then developed to solve the fuzzy bi-level programming problem based on different compromised selections by decision entities on the feasible degree for constraint conditions under fuzziness. Lastly, an illustrative numerical example and two benchmark examples are adopted to state the effectiveness of the compromise-based PSO algorithm.
Please use this identifier to cite or link to this item: