MOEA toolbox for computer aided multi-objective optimization

K. C. Tan, T. H. Lee, D. Khoo, E. F. Khor, R. Sathi Kannan

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review

9 Citations (Scopus)

Abstract

This paper presents a comprehensive Graphical User Interface (GUI) based MOEA Toolbox that implements Multi-Objective Evolutionary Algorithm (MOEA). The toolbox incorporates Pareto cost assignment scheme and other complementary features of hard constraint specification for constraint handling, dynamic population size, fuzzy boundary local perturbation with interactive local fine-tuning, a novel switching preserved strategy and convergence representation for multi-objective optimization. The user only needs a little programming knowledge to write the model file. Other aspects of the simulation like the settings, process monitoring and results analysis are performed on user-friendly and user-interactive GUI windows with easy-to-understand on-line help files. The MOEA Toolbox's performance in a benchmark problem and an actual application has been presented as a demonstration of the toolbox's capabilities.
Original languageEnglish
Title of host publicationProceedings of the 2000 Congress on Evolutionary Computation, CEC 2000
PublisherIEEE
Pages38-45
Volume1
ISBN (Print)0-7803-6375-2
DOIs
Publication statusPublished - Jul 2000
Externally publishedYes
Event2000 Congress on Evolutionary Computation, CEC 2000 - San Diego, CA, United States
Duration: 16 Jul 200019 Jul 2000

Publication series

Name
Volume1

Conference

Conference2000 Congress on Evolutionary Computation, CEC 2000
PlaceUnited States
CitySan Diego, CA
Period16/07/0019/07/00

Fingerprint

Dive into the research topics of 'MOEA toolbox for computer aided multi-objective optimization'. Together they form a unique fingerprint.

Cite this