Parallel Line-Up Competition Algorithm for Continuous Optimization

Abstract:

This paper presents a new parallel line-up competition algorithm (PLCA) for solving continuous optimization problems. A coarse-grained parallel model has been used to implement the PLCA. In this model, the whole family is equally divided into several subfamily groups that evolve independently in single processor. When migration condition is reached, a portion of fit families in each subfamily group migrate to the neighboring node according to a ring migration topology. The proposed algorithm has been evaluated by solving a set of well-known test functions. Simulation results show that PLCA has good parallel efficiency and superior performance.

• Periodical: Applied Mechanics and Materials (Volumes 20-23)
• Pages: 161-166
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.20-23.161
• Online since: January 2010
• Authors: Bin Shi, Lie Xiang Yan, Hui Xie
• Keywords: Coarse-Grained Model, Continuous Optimization, Evolutionary Algorithm (EA), Parallel Line-Up Competition Algorithm

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