An Improved Thermodynamics Evolutionary Algorithm Based on the Minimal Free Energy

Yu, Fahong; Li, Yuanxiang; Ying, Weiqin

doi:10.1007/978-3-642-13495-1_66

Cited by 2 publications

(1 citation statement)

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“…Therefore, we can alleviate the conflict between the selective pressure and the diversity of population according to the principle of the minimal free energy. Inspired by [41][42][43], in the improved selection scheme, we firstly map the selective pressure and the population diversity of DE into the mean energy E and the entropy H in the principle of the minimal free energy, respectively. Then, the criterion of the proposed selection scheme is converted to the minimal free energy, which means that we select individuals for the next generation from the parent, and the offspring population should satisfy the principle of the minimal free energy.…”

Section: Motivationsmentioning

confidence: 99%

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

Guo

Yue

Zhang

et al. 2014

Entropy

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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.

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Section: Motivationsmentioning

confidence: 99%