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
Open AccessArticle

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.
Entropy 2014, 16(12), 6263-6285; https://doi.org/10.3390/e16126263
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)
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
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

Article Access Map by Country/Region

1
Only visits after 24 November 2015 are recorded.
Search more from Scilit
 
Search
Back to TopTop