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A Study of Heterogeneous Swarm Approaches

作者:???
畢業學校:國立高雄大學
出版單位:國立高雄大學
核准日期:2015-09-09
類型:Electronic Thesis or Dissertation
權限:Copyright information available at source archive--National University of Kaohsiung....

中文摘要

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英文摘要

Biologically-inspired computing is very popular in recent years since it can solve most of optimization problems very efficiently. Although the solutions obtained are not certainly optimal, they are usually acceptable for real applications. Among the strategies for this type of computing, the ant colony optimization (ACO) strategy and the genetic algorithm (GA) are very commonly used. They, however, use different mechanisms to solve problems. ACO uses the cooperative search of the ant-like behavior to find good solutions, but GA uses the principle of survival to generate answers. Since the two strategies have their own advantages in solving problems, we thus attempt to integrate them to increase the search diversity in this thesis. We expect the solution quality can be raised as well due to more diversity. Several approaches are thus proposed. In the first approach, the ACO is first executed, and then GA. The two approaches are performed in their own mechanisms. When a predefined iteration number is reached, the two approaches exchange a fixed amount of the best individuals to each other, and the same process is repeated until the termination criterion is met. A transformation strategy between the two different representations of solutions is designed as well. Besides, it can be easily modified as GA before ACS. Some variants from the first approach are then proposed. The execution architecture is very suitable for parallelization in nature. Experiments are also made to show the performance of the proposed approach.


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