We apologize for a recent technical issue with our email system, which temporarily affected account activations. Accounts have now been activated. Authors may proceed with paper submissions. PhDFocusTM
CFP last date
20 November 2024
Reseach Article

Differential Evolution based Multiobjective Optimization-A Review

by Deepa Sreedhar, Binu Rajan M .r
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 63 - Number 15
Year of Publication: 2013
Authors: Deepa Sreedhar, Binu Rajan M .r
10.5120/10541-5019

Deepa Sreedhar, Binu Rajan M .r . Differential Evolution based Multiobjective Optimization-A Review. International Journal of Computer Applications. 63, 15 ( February 2013), 14-19. DOI=10.5120/10541-5019

@article{ 10.5120/10541-5019,
author = { Deepa Sreedhar, Binu Rajan M .r },
title = { Differential Evolution based Multiobjective Optimization-A Review },
journal = { International Journal of Computer Applications },
issue_date = { February 2013 },
volume = { 63 },
number = { 15 },
month = { February },
year = { 2013 },
issn = { 0975-8887 },
pages = { 14-19 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume63/number15/10541-5019/ },
doi = { 10.5120/10541-5019 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:14:35.804676+05:30
%A Deepa Sreedhar
%A Binu Rajan M .r
%T Differential Evolution based Multiobjective Optimization-A Review
%J International Journal of Computer Applications
%@ 0975-8887
%V 63
%N 15
%P 14-19
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Multiobjective differential evolution(MDE) is a powerful, stochastic multi objective optimization(MOO) algorithm based on Differential Evolution(DE) that aims to optimize a problem that involves multiple objective functions. The MDE has many applications in the real world including supply chain planning and management. This paper presents a review of some multi objective (back propagation) differential evolution algorithms.

References
  1. B. V Babu, and Mathew, L. J. 2003. "Differential Evolu-tion for Multi-Objective Optimization". (Dec 2003), 2696–2703.
  2. Nateri, K. M. 2002. "Multiobjective Optimization Using a Pareto Differential Evolution Approach". (May 2002), 1145–1150.
  3. Luis, V. S. and Carlos, A. C. C. 2005. "An Algorithm Based on Differential Evolution for Multi-Objective Problems". 151–169.
  4. Wenyin, G. and Zhihua C. A. 2008. "Multiobjective Differential Evolution Algorithm for Constrained Opti-mization". 182-188.
  5. Ashish, M. G. B V Babu. Improved Strategies of Multi-objective Differential Evolution (MODE) for Multi-objective Optimization.
  6. R. Storn and K. Price. 1995 "Differential evolution: a simple and efficient adaptive scheme for global optimiza-tion over continuous spaces".
  7. Ales Z, Janez B, Borko B, and Viljem Z. 2007. "Diffe-rential Evolution for Multiobjective Optimization with Self Adaptation". 3617-3624.
  8. Tea R and Bogdan F. 2005 "DEMO: Differential Evolu-tion for Multiobjective Optimization. pages". 520-523.
  9. B. V. Babu, Ashish M. G. 2007. "Elitist- Multi-objective Differential Evolution(MODE) algorithm for Multi-objective Optimization. 441-456.
  10. K. E. Parsopoulos, D. K. Taoulis, N. G. Pavlidis, V. P. Plagianakos, and M. N. Vrahatis. 2004. "Vector Evaluated Differential Evolution for Multiobjective Optimization". (June 2004), 204–211.
  11. J. D. Schaffer. 1984. "Multiple Objective Optimization With Vector Evaluated Genetic Algorithms".
  12. Antony W. L. and Xiaodong L. 2004. "Solving rotated multi-objective optimization problems using differential evolution". 861–872.
  13. Kalyanmoy, D. Amrit, P. Sameer, A. and T. Meyarivan. "A Fast and Elitist Multiobjective Genetic Algorithm: NSGA-II". (April 2002) , 182-197.
  14. Efren M. M, Margarita R. S. ,Carlos A. C. C. "Multi-Objective Optimization using Differential Evolution: A Survey of the State-of-the-Art".
Index Terms

Computer Science
Information Sciences

Keywords

Differential Evolution Non-dominated sorting orthogonal crossover Fitness sharing random selection elitist selection