Multi-Objective Particle Swarm Optimization using Generalized Data Envelopment Analysis

• Yun Yeboon

  Faculty of Environmental and Urban Engineering, Kansai University

• Nakayama Hirotaka

  Department of Intelligence and Informatics, Konan University

Bibliographic Information

Other Title

• 一般化包絡分析法を用いた多目的ＰＳＯ法
• イッパンカ ホウラクブンセキホウ オ モチイタ タモクテキ PSOホウ

Abstract

Several meta-heuristic methods such as genetic algorithms and particle swarm optimization (PSO) have been applied for solving multi-objective optimization problems, and have been observed to be useful for generating the whole Pareto optimal solutions. In this research, we propose a new method of multi-objective particle swarm optimization by using generalized data envelopment analysis (GDEA) in order to improve the convergence and the diversity when searching for the solutions as well as to decide easily parameters in PSO. In addition, we investigate the effectiveness of the proposed PSO method using GDEA through some numerical examples. <br>

Journal

• Transactions of the Institute of Systems, Control and Information Engineers

  Transactions of the Institute of Systems, Control and Information Engineers 23 (9), 215-222, 2010

  THE INSTITUTE OF SYSTEMS, CONTROL AND INFORMATION ENGINEERS (ISCIE)

Keywords

• multi-objective optimization
• Pareto optimal solution
• particle swarm optimization
• generalized data envelopment analysis

Details

• CRID: 1390282680141476992
• NII Article ID: 10027615330
• NII Book ID: AN1013280X
• DOI: 10.5687/iscie.23.215
• ISSN: 2185811X
• ISSN: 13425668
• NDL BIB ID: 10817601
• Web Site: https://ndlsearch.ndl.go.jp/books/R000000004-I10817601
• Text Lang: ja
• Data Source:
  • JaLC
  • NDL
  • Crossref
  • CiNii Articles
  • KAKEN
• Abstract License Flag: Disallowed