A Parallel Optimization Algorithm Based on Communication Strategy of Pollens and Agents
作者： Pei-Wei Tsai , Trong-The Nguyen , Jeng-Shyang Pan , Thi-Kien Dao , Wei-Min Zheng
DOI: 10.1007/978-3-319-50212-0_38
关键词:
摘要: Unwanted convergence to a local optimum, rather than global is possible take place in practical multimodal optimization problems. Communication between artificial agents the stochastic algorithms one of solutions this issue. This paper proposes novel parallel algorithm, namely FDA, based on communication pollen Flower pollination algorithm (FPA) with Differential evolution (DEA) solve A strategy for Pollens and Agents advantages strength points each explore exploit diversity avoiding dropping optimum. set benchmark functions used test quality performance proposed algorithm. Simulation results show that in-creases accuracy more existing algorithms.
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