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

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

Institute of Medical Informatics and Engineering, School of Science, JiangXi University of Science and Technology, Ganzhou 341000, China
College of Computer Science and Technology, Zhejiang University, Hangzhou 310027, China
School of Information Engineering, Shijiazhuang University of Economics, Shijiazhuang 050031, China
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)
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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).

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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.

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