The Science and Information (SAI) Organization
  • Home
  • About Us
  • Journals
  • Conferences
  • Contact Us

Publication Links

  • IJACSA
  • Author Guidelines
  • Publication Policies
  • Digital Archiving Policy
  • Promote your Publication
  • Metadata Harvesting (OAI2)

IJACSA

  • About the Journal
  • Call for Papers
  • Editorial Board
  • Author Guidelines
  • Submit your Paper
  • Current Issue
  • Archives
  • Indexing
  • Fees/ APC
  • Reviewers
  • Apply as a Reviewer

IJARAI

  • About the Journal
  • Archives
  • Indexing & Archiving

Special Issues

  • Home
  • Archives
  • Proposals
  • Guest Editors
  • SUSAI-EE 2025
  • ICONS-BA 2025
  • IoT-BLOCK 2025

Future of Information and Communication Conference (FICC)

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Computing Conference

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Intelligent Systems Conference (IntelliSys)

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Future Technologies Conference (FTC)

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact
  • Home
  • Call for Papers
  • Editorial Board
  • Guidelines
  • Submit
  • Current Issue
  • Archives
  • Indexing
  • Fees
  • Reviewers
  • Subscribe

DOI: 10.14569/IJACSA.2016.070274
PDF

Evolutionary Algorithms Based on Decomposition and Indicator Functions: State-of-the-art Survey

Author 1: Wali Khan Mashwani
Author 2: Abdellah Salhi
Author 3: Muhammad Asif jan
Author 4: Muhammad Sulaiman
Author 5: Rashida Adeeb Khanum
Author 6: Abdulmohsen Algarni

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 7 Issue 2, 2016.

  • Abstract and Keywords
  • How to Cite this Article
  • {} BibTeX Source

Abstract: In the last two decades, multiobjective optimization has become mainstream because of its wide applicability in a variety of areas such engineering, management, the military and other fields. Multi-Objective Evolutionary Algorithms (MOEAs) play a dominant role in solving problems with multiple conflicting objective functions. They aim at finding a set of representative Pareto optimal solutions in a single run. Classical MOEAs are broadly in three main groups: the Pareto dominance based MOEAs, the Indicator based MOEAs and the decomposition based MOEAs. Those based on decomposition and indicator functions have shown high search abilities as compared to the Pareto dominance based ones. That is possibly due to their firm theoretical background. This paper presents state-of-the-art MOEAs that employ decomposition and indicator functions as fitness evaluation techniques along with other efficient techniques including those which use preference based information, local search optimizers, multiple ensemble search operators together with self-adaptive strategies, metaheuristics, mating restriction approaches, statistical sampling techniques, integration of Fuzzy dominance concepts and many other advanced techniques for dealing with diverse optimization and search problems

Keywords: Multi-objective optimization, Multi-objective Evolu-tionary algorithms (MOEAs), Pareto Optimality, Multi-objective Memetic Algorithm (MOMAs), Pareto dominance based MOEA, Decomposition based MOEA, Indicator based MOEAs

Wali Khan Mashwani, Abdellah Salhi, Muhammad Asif jan, Muhammad Sulaiman, Rashida Adeeb Khanum and Abdulmohsen Algarni, “Evolutionary Algorithms Based on Decomposition and Indicator Functions: State-of-the-art Survey” International Journal of Advanced Computer Science and Applications(IJACSA), 7(2), 2016. http://dx.doi.org/10.14569/IJACSA.2016.070274

@article{Mashwani2016,
title = {Evolutionary Algorithms Based on Decomposition and Indicator Functions: State-of-the-art Survey},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2016.070274},
url = {http://dx.doi.org/10.14569/IJACSA.2016.070274},
year = {2016},
publisher = {The Science and Information Organization},
volume = {7},
number = {2},
author = {Wali Khan Mashwani and Abdellah Salhi and Muhammad Asif jan and Muhammad Sulaiman and Rashida Adeeb Khanum and Abdulmohsen Algarni}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

IJACSA

Upcoming Conferences

IntelliSys 2025

28-29 August 2025

  • Amsterdam, The Netherlands

Future Technologies Conference 2025

6-7 November 2025

  • Munich, Germany

Healthcare Conference 2026

21-22 May 2026

  • Amsterdam, The Netherlands

Computing Conference 2026

9-10 July 2026

  • London, United Kingdom

IntelliSys 2026

3-4 September 2026

  • Amsterdam, The Netherlands

Computer Vision Conference 2026

15-16 October 2026

  • Berlin, Germany
The Science and Information (SAI) Organization
BACK TO TOP

Computer Science Journal

  • About the Journal
  • Call for Papers
  • Submit Paper
  • Indexing

Our Conferences

  • Computing Conference
  • Intelligent Systems Conference
  • Future Technologies Conference
  • Communication Conference

Help & Support

  • Contact Us
  • About Us
  • Terms and Conditions
  • Privacy Policy

© The Science and Information (SAI) Organization Limited. All rights reserved. Registered in England and Wales. Company Number 8933205. thesai.org