Differential Evolution Using Opposite Point for Global Numerical Optimization

Ao, Youyun; Chi, Hongqin

doi:10.4236/jilsa.2012.41001

Cited by 3 publications

(2 citation statements)

References 25 publications

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“…A set of 13 well-known benchmark functions, listed in Table 1, was used in this experiment [33,38]. The number of dimensions (i.e., n in Table 1) of the search space is set to 30.…”

Section: Experiments Settingsmentioning

confidence: 99%

Interaction Enhanced Imperialist Competitive Algorithms

Lin

Tsai

et al. 2012

Algorithms

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Imperialist Competitive Algorithm (ICA) is a new population-based evolutionary algorithm. It divides its population of solutions into several sub-populations, and then searches for the optimal solution through two operations: assimilation and competition. The assimilation operation moves each non-best solution (called colony) in a sub-population toward the best solution (called imperialist) in the same sub-population. The competition operation removes a colony from the weakest sub-population and adds it to another sub-population. Previous work on ICA focuses mostly on improving the assimilation operation or replacing the assimilation operation with more powerful meta-heuristics, but none focuses on the improvement of the competition operation. Since the competition operation simply moves a colony (i.e., an inferior solution) from one sub-population to another sub-population, it incurs weak interaction among these sub-populations. This work proposes Interaction Enhanced ICA that strengthens the interaction among the imperialists of all sub-populations. The performance of Interaction Enhanced ICA is validated on a set of benchmark functions for global optimization. The results indicate that the performance of Interaction Enhanced ICA is superior to that of ICA and its existing variants.

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“…A set of 13 well-known benchmark functions, listed in Table 1, was used in this experiment [33,38]. The number of dimensions (i.e., n in Table 1) of the search space is set to 30.…”

Section: Experiments Settingsmentioning

confidence: 99%

Interaction Enhanced Imperialist Competitive Algorithms

Lin

Tsai

et al. 2012

Algorithms

View full text Add to dashboard Cite

show abstract

“…DE can also offer a high degree of variations for the population to search the solution. It has been successfully applied in a number of optimization benchmark functions [9] and in a wide range of optimization problems such as data clustering [10], power plant control [11], optimization of nonlinear functions [12], electromagnetic inverse scattering problems [13], etc. However, for maintaining the diversity from one generation of population to the next, mutation takes an important role in the evolution process.…”

Section: Introductionmentioning

confidence: 99%

An Improved Differential Evolution and Its Industrial Application

Lai¹,

Leung²,

Ling³

et al. 2012

JILSA

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In this paper, an improved Differential Evolution (DE) that incorporates double wavelet-based operations is proposed to solve the Economic Load Dispatch (ELD) problem. The double wavelet mutations are applied in order to enhance DE in exploring the solution space more effectively for better solution quality and stability. The first stage of wavelet operation is embedded in the DE mutation operation, in which the scaling factor is governed by a wavelet function. In the second stage, a wavelet-based mutation operation is embedded in the DE crossover operation. The trial population vectors are modified by the wavelet function. A suite of benchmark test functions is employed to evaluate the performance of the proposed DE in different problems. The result shows empirically that the proposed method out-performs signifycantly the conventional methods in terms of convergence speed, solution quality and solution stability. Then the proposed method is applied to the Economic Load Dispatch with Valve-Point Loading (ELD-VPL) problem, which is a process to share the power demand among the online generators in a power system for minimum fuel cost. Two different conditions of the ELD problem have been tested in this paper. It is observed that the proposed method gives satisfactory optimal costs when compared with the other techniques in the literature

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An ensemble belief rule base model for pathologic complete response prediction in gastric cancer

Wang

et al. 2023

Expert Systems with Applications

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Differential Evolution Using Opposite Point for Global Numerical Optimization

Cited by 3 publications

References 25 publications

Interaction Enhanced Imperialist Competitive Algorithms

Interaction Enhanced Imperialist Competitive Algorithms

An Improved Differential Evolution and Its Industrial Application

An ensemble belief rule base model for pathologic complete response prediction in gastric cancer

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