Property | Value |
Name | NCL-TR-2006006 |
Description |
Introducing Recombination with Dynamic Linkage Discovery to Particle Swarm Optimization
Abstract: There are two main objectives in this thesis. The first goal is to improve the performance of the particle swarm optimizer by incorporating linkage concept which is an essential mechanism in genetic algorithms. To achieve this purpose, we need to know the characteristics of the particle swarm optimizer and the genetic linkage problem. Through survey of the particle swarm optimization and the linkage problem, we then figure out how to introduce the linkage concept to particle swarm optimizer. Another goal is to address the linkage problem in real-parameter optimization problems. We have to study different linkage learning techniques, and understand the meaning of genetic linkage in real-parameter problems. After that, we design a novel linkage identification technique to achieve this objective. In this thesis, the existence of genetic linkages in real-parameter optimization problem and that genetic linkages are dynamically changed through the search process are the primary assumptions. With these assumptions, we develop the dynamic linkage discovery technique to address the linkage problem. Moreover, a special recombination operator is designed to promote the cooperation of particle swarm optimizer and linkage identification technique. In the consequence, we introduce the recombination operator with the technique of dynamic linkage discovery to particle swarm optimization (PSO). Dynamic linkage discovery is a costless, effective linkage recognition technique adapting the linkage configuration by utilizing the natural selection without incorporating extra judging criteria irrelevant to the objective function. Furthermore, we employ a specific recombination operator to work with the building blocks identified by dynamic linkage discovery. The whole framework forms a new efficient search algorithm and is called PSO-RDL in this study. Numerical experiments are conducted on a set of carefully designed benchmark functions and demonstrate good performance achieved by the proposed methodology. Moreover, we also applied the proposed algorithm on the economic dispatch problem which is an essential topic in power control systems. The experimental results show that PSO-RDL can performs well both on numerical benchmark and real-world applications. |
Filename | NCL-TR-2006006.pdf |
Filesize | 752.49 kB |
Filetype | pdf (Mime Type: application/pdf) |
Creator | ypchen |
Created On: | 07/23/2006 01:44 |
Viewers | Everybody |
Maintained by | Publisher |
Hits | 4535 Hits |
Last updated on | 12/09/2010 15:00 |
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