Next Article in Journal
Adaptive Synchronization of Fractional Neural Networks with Unknown Parameters and Time Delays
Next Article in Special Issue
Application of the Permutation Entropy over the Heart Rate Variability for the Improvement of Electrocardiogram-based Sleep Breathing Pause Detection
Previous Article in Journal
On a Local Fractional Wave Equation under Fixed Entropy Arising in Fractal Hydrodynamics
Previous Article in Special Issue
Application of Entropy and Fractal Dimension Analyses to the Pattern Recognition of Contaminated Fish Responses in Aquaculture
Article Menu

Export Article

Open AccessArticle
Entropy 2014, 16(12), 6263-6285; doi:10.3390/e16126263

A Thermodynamical Selection-Based Discrete Differential Evolution for the 0-1 Knapsack Problem

1
Institute of Medical Informatics and Engineering, School of Science, JiangXi University of Science and Technology, Ganzhou 341000, China
2
College of Computer Science and Technology, Zhejiang University, Hangzhou 310027, China
3
School of Information Engineering, Shijiazhuang University of Economics, Shijiazhuang 050031, China
4
State Key Laboratory of Software Engineering, Wuhan University, Wuhan 430072, China
*
Author to whom correspondence should be addressed.
Received: 2 October 2014 / Revised: 8 November 2014 / Accepted: 21 November 2014 / Published: 28 November 2014
(This article belongs to the Special Issue Entropy in Bioinspired Intelligence)
View Full-Text   |   Download PDF [266 KB, uploaded 24 February 2015]   |  

Abstract

Many problems in business and engineering can be modeled as 0-1 knapsack problems. However, the 0-1 knapsack problem is one of the classical NP-hard problems. Therefore, it is valuable to develop effective and efficient algorithms for solving 0-1 knapsack problems. Aiming at the drawbacks of the selection operator in the traditional differential evolution (DE), we present a novel discrete differential evolution (TDDE) for solving 0-1 knapsack problem. In TDDE, an enhanced selection operator inspired by the principle of the minimal free energy in thermodynamics is employed, trying to balance the conflict between the selective pressure and the diversity of population to some degree. An experimental study is conducted on twenty 0-1 knapsack test instances. The comparison results show that TDDE can gain competitive performance on the majority of the test instances. View Full-Text
Keywords: differential evolution; discrete optimization; thermodynamical selection; 0-1 knapsack problem differential evolution; discrete optimization; thermodynamical selection; 0-1 knapsack problem
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

Guo, Z.; Yue, X.; Zhang, K.; Wang, S.; Wu, Z. A Thermodynamical Selection-Based Discrete Differential Evolution for the 0-1 Knapsack Problem. Entropy 2014, 16, 6263-6285.

Show more citation formats Show less citations formats

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Entropy EISSN 1099-4300 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top