Next Article in Journal
A Two-Stage Method to Test the Robustness of the Generalized Approximate Message Passing Algorithm
Next Article in Special Issue
Elite Opposition-Based Social Spider Optimization Algorithm for Global Function Optimization
Previous Article in Journal
Algorithms for Drug Sensitivity Prediction
Previous Article in Special Issue
A Variable Block Insertion Heuristic for the Blocking Flowshop Scheduling Problem with Total Flowtime Criterion
Article Menu

Export Article

Open AccessArticle
Algorithms 2016, 9(4), 78; doi:10.3390/a9040078

A Modified Cloud Particles Differential Evolution Algorithm for Real-Parameter Optimization

School of Computer Science and Engineering, Xi’an University of Technology, Xi’an 710048, China
Academic Editor: Yun-Chia Liang
Received: 18 July 2016 / Revised: 2 November 2016 / Accepted: 14 November 2016 / Published: 18 November 2016
(This article belongs to the Special Issue Metaheuristic Algorithms in Optimization and Applications)
View Full-Text   |   Download PDF [811 KB, uploaded 21 November 2016]   |  

Abstract

The issue of exploration-exploitation remains one of the most challenging tasks within the framework of evolutionary algorithms. To effectively balance the exploration and exploitation in the search space, this paper proposes a modified cloud particles differential evolution algorithm (MCPDE) for real-parameter optimization. In contrast to the original Cloud Particles Differential Evolution (CPDE) algorithm, firstly, control parameters adaptation strategies are designed according to the quality of the control parameters. Secondly, the inertia factor is introduced to effectively keep a better balance between exploration and exploitation. Accordingly, this is helpful for maintaining the diversity of the population and discouraging premature convergence. In addition, the opposition mechanism and the orthogonal crossover are used to increase the search ability during the evolutionary process. Finally, CEC2013 contest benchmark functions are selected to verify the feasibility and effectiveness of the proposed algorithm. The experimental results show that the proposed MCPDE is an effective method for global optimization problems. View Full-Text
Keywords: cloud particles differential evolution; exploration-exploitation; inertia factor; global optimization cloud particles differential evolution; exploration-exploitation; inertia factor; global optimization
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Li, W. A Modified Cloud Particles Differential Evolution Algorithm for Real-Parameter Optimization. Algorithms 2016, 9, 78.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Algorithms EISSN 1999-4893 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top