Binary Encoding Differential Evolution with Application to Combinatorial Optimization Problem

Deng, Changshou; Zhao, Bingyan; Yang, Yanlin; Hai, Zhang

doi:10.1007/978-3-642-38460-8_9

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Discretisation Approaches For Metaheuristics1

Angle Modulation1

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2016

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Cited by 2 publications

(2 citation statements)

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“…The first one consists of substituting the arithmetic operators in the algorithm by logical ones [22,41,96,102], while the second subcategory consists of finding the corresponding geometric interpretation of the algorithm's operators in Hamming space [8][9][10]. The final subcategory regroups some isolated strategies that have been proposed in the literature, but none of them followed one of the above-mentioned two subcategories [16,17,101]. Nevertheless, the use of this first approach is still limited to some specific metaheuristics, and thus cannot be applied to all algorithms.…”

Section: Discretisation Approaches For Metaheuristicsmentioning

confidence: 98%

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On the efficiency of the binary flower pollination algorithm: Application on the antenna positioning problem

Dahi

Mezioud

Draa

2016

Applied Soft Computing

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Section: Discretisation Approaches For Metaheuristicsmentioning

confidence: 98%

“…The elements of latter are drawn from the interval [0,1] and have equally-spaced intervals between one and another. Secondly, the condition represented by Formula (16) is applied on the solution vector X G in order to produce X B . …”

Section: Angle Modulationmentioning

confidence: 99%

On the efficiency of the binary flower pollination algorithm: Application on the antenna positioning problem

Dahi

Mezioud

Draa

2016

Applied Soft Computing

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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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Binary Encoding Differential Evolution with Application to Combinatorial Optimization Problem

Cited by 2 publications

References 4 publications

On the efficiency of the binary flower pollination algorithm: Application on the antenna positioning problem

On the efficiency of the binary flower pollination algorithm: Application on the antenna positioning problem

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

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