A multipopulation cultural algorithm for the electrical generator scheduling problem

Digalakis, Jason G.; Margaritis, Konstantinos G.

doi:10.1016/s0378-4754(02)00021-6

Cited by 44 publications

(9 citation statements)

References 12 publications

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“…Moreover, this kind of optimization problem is hard, if not impossible, to solve using deterministic optimization algorithms. Recently, as an alternative to the conventional optimization approaches, modern stochastic optimization techniques based on evolutionary algorithms (EAs) [5,7,8,10,11,14,16,31,35,37] have been given much attention by many researchers due to their ability to find potential solutions.…”

Section: Introductionmentioning

confidence: 99%

Improved differential evolution approach based on cultural algorithm and diversity measure applied to solve economic load dispatch problems

Coelho

Souza

Mariani

2009

Mathematics and Computers in Simulation

123

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Section: Introductionmentioning

confidence: 99%

Improved differential evolution approach based on cultural algorithm and diversity measure applied to solve economic load dispatch problems

Coelho

Souza

Mariani

2009

Mathematics and Computers in Simulation

123

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“…There are several variants and application can be found in the literature (Digalakis and Margaritis 2002;Alexiou and Vlamos 2012;Ochoa-Zezzatti et al 2012;Srinivasan and Ramakrishnan 2012;Silva et al 2012). In CA, the evolution process can be viewed as a dual-inheritance system in which two search spaces (i.e., the population space and the belief space) are included.…”

Section: Fundamentals Of Cultural Algorithmmentioning

confidence: 99%

Emerging Biology-based CI Algorithms

Xing

Gao²

2013

Innovative Computational Intelligence: A Rough Guide to 134 Clever Algorithms

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In this chapter, a group of (more specifically 56 in total) emerging biology-based computational intelligence (CI) algorithms are introduced. We first, in Sect. 17.1, describe the organizational structure of this chapter. Then, from Sects. 17.2 to 17.57, each section is dedicated to a specific algorithm which falls within this category, respectively. The fundamentals of each algorithm and their corresponding performances compared with other CI algorithms can be found in each associated section. Finally, the conclusions drawn in Sect. 17.58 closes this chapter.

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“…The algorithm's performance with different parameters are compared and analyzed. And it is compared with traditional cultural algorithm (CA) and multi-population cultural algorithm adopting individual migration (MCAIM) (Digalakis and Margaritis 2002).…”

Section: Simulation and Analysismentioning

confidence: 99%

“…Researches about how to reasonably use implicit knowledge in multi-population cultural algorithms are seldom taken into account. Aiming at the electric dispatch problems, Digalakis and Margaritis (2002) proposed the multi-population cultural algorithm adopting individual migration. In the algorithm, only best solutions coming from each sub-population are exchanged in terms of given migration rules.…”

Section: Introductionmentioning

confidence: 99%

A novel multi-population cultural algorithm adopting knowledge migration

et al. 2010

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In existing multi-population cultural algorithms, information is exchanged among sub-populations by individuals. However, migrated individuals cannot reflect enough evolutionary information, which limits the evolution performance. In order to enhance the migration efficiency, a novel multi-population cultural algorithm adopting knowledge migration is proposed. Implicit knowledge extracted from the evolution process of each sub-population directly reflects the information about dominant search space. By migrating knowledge among sub-populations at the constant intervals, the algorithm realizes more effective interaction with less communication cost. Taken benchmark functions with high-dimension as the examples, simulation results indicate that the algorithm can effectively improve the speed of convergence and overcome premature convergence.

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A multipopulation cultural algorithm for the electrical generator scheduling problem

Cited by 44 publications

References 12 publications

Improved differential evolution approach based on cultural algorithm and diversity measure applied to solve economic load dispatch problems

Improved differential evolution approach based on cultural algorithm and diversity measure applied to solve economic load dispatch problems

Emerging Biology-based CI Algorithms

A novel multi-population cultural algorithm adopting knowledge migration

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