岑雪婷, 唐智勇, 杨勇. 采用改进的细菌觅食优化算法求解RCPSP[J]. 微电子学与计算机, 2013, 30(10): 90-92,96.
引用本文: 岑雪婷, 唐智勇, 杨勇. 采用改进的细菌觅食优化算法求解RCPSP[J]. 微电子学与计算机, 2013, 30(10): 90-92,96.
CEN Xueting, TANG Zhiyong, YANG Yong. Proving Bacterial Foraging Optimization Algorithm for RCPSP[J]. Microelectronics & Computer, 2013, 30(10): 90-92,96.
Citation: CEN Xueting, TANG Zhiyong, YANG Yong. Proving Bacterial Foraging Optimization Algorithm for RCPSP[J]. Microelectronics & Computer, 2013, 30(10): 90-92,96.

采用改进的细菌觅食优化算法求解RCPSP

Proving Bacterial Foraging Optimization Algorithm for RCPSP

  • 摘要: 针对细菌觅食优化算法全局搜索能力较弱和收敛速度慢的问题,对算法的更新方式进行改进,在算法的初期通过粒子群算法进行全局搜索,使细菌在更新时感知周围环境,再由细菌觅食算法的趋向操作进行局部搜索,提高算法的计算精度和搜索能力。最后运用实例对算法进行验证,实验结果验证了此算法在求解资源受限的项目调度问题时的可行性和优越性。

     

    Abstract: Based on the analysis of former algorithms about the Resource-Constrainted Project Scheduling Problem,a new intelligent optimization algorithm-bacterial foraging optimization(BFO) algorithm is presented.Considering the shortage of the BFO algorithm, the algorithm's update method is improved. In order to improve the search capabilities and calculation accuracy of BFO, the algorithm used PSO for global search firstly, then the trend operation of BFO was used for local search,each bacterium adjusts its position according to the position of the neighborhood bacteria.Computational analyses are represented to verify the effective of the proposed methodology.

     

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