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.

The differential evolution (DE) algorithm is a popular and efficient evolutionary algorithm that can be used for single objective real-parameter optimization. Its performance is greatly affected by its parameters. Generally, parameter control strategies involve determining the most suitable value for the current state; there is only a little research on parameter combination and parameter distribution which is also useful for improving algorithm performance. This paper proposes an idea to use parameter region division and parameter strategy combination to flexibly adjust the parameter distribution. Based on the idea, a group-based two-level parameter combination framework is designed to support various modes of parameter combination, and enrich the parameter distribution characteristics. Under this framework, two customized parameter combination strategies are given for a single-operation DE algorithm and a multi-operation DE algorithm. The experiments verify the effectiveness of the two strategies and it also illustrates the meaning of the framework.