A General Intelligent Optimization Algorithm Combination Framework with Application in Economic Load Dispatch Problems

Jinghua Zhang and Ze Dong
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Jinghua Zhang: Hebei Engineering Research Center of Simulation Optimized Control for Power Generation, North China Electric Power University, Baoding 071003, China
Ze Dong: Hebei Engineering Research Center of Simulation Optimized Control for Power Generation, North China Electric Power University, Baoding 071003, China

Energies, 2019, vol. 12, issue 11, 1-22

Abstract: Recently, a population-based intelligent optimization algorithm research has been combined with multiple algorithms or algorithm components in order to improve the performance and robustness of an optimization algorithm. This paper introduces the idea into real world application. Different from traditional algorithm research, this paper implements this idea as a general framework. The combination of multiple algorithms or algorithm components is regarded as a complex multi-behavior population, and a unified multi-behavior combination model is proposed. A general agent-based algorithm framework is designed to support the model, and various multi-behavior combination algorithms can be customized under the framework. Then, the paper customizes a multi-behavior combination algorithm and applies the algorithm to solve the economic load dispatch problems. The algorithm has been tested with four test systems. The test results prove that the multi-behavior combination idea is meaningful which also indicates the significance of the framework.

Keywords: population-based intelligent optimization algorithm; multi-behavior combination; algorithm framework; Economic load dispatch (ELD) (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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