孙晓雅, 林焰. 改进的人工蜂群算法求解任务指派问题[J]. 微电子学与计算机, 2012, 29(1): 23-26.
引用本文: 孙晓雅, 林焰. 改进的人工蜂群算法求解任务指派问题[J]. 微电子学与计算机, 2012, 29(1): 23-26.
SUN Xiao-ya, LIN Yan. Improved Artificial Bee Colony Algorithm for Assignment Problem[J]. Microelectronics & Computer, 2012, 29(1): 23-26.
Citation: SUN Xiao-ya, LIN Yan. Improved Artificial Bee Colony Algorithm for Assignment Problem[J]. Microelectronics & Computer, 2012, 29(1): 23-26.

改进的人工蜂群算法求解任务指派问题

Improved Artificial Bee Colony Algorithm for Assignment Problem

  • 摘要: 针对指派问题提出了一种改进的人工蜂群算法.该算法充分考虑到指派问题解的离散性特点, 给出了食物源位置的离散编码方法, 并且采用邻域移动法生成候选食物源, 这一方法既保证了解的可行性, 又增加了食物源的多样性.实算表明在求解指派问题时, 该算法比原人工蜂群算法在求解精度和收敛速度上都有显著地提高, 两性能也优于其他粒子群算法.这种改进的离散人工蜂群算法简洁, 应用方便, 不但是一种有效求解指派问题的新算法, 同时也为其他组合优化问题求解提供了一种有益思路.

     

    Abstract: An improved artificial bee colony (IABC) optimization algorithm is presented for assignment problem.In consideration of the solution's discreteness, this algorithm gives a discrete coding method for the food source position.The algorithm adopts neighborhood shift to produce a candidate food position, which can ensure the solution feasible and increase the diversity of food sources.The actual calculation shows that the IABC algorithm can accelerate the convergence process obviously and improve the precision compared with the original artificial bee colony (ABC) algorithm, and this method is also superior to other particle swarm optimization (PSO) algorithms.The principle of this algorithm is simple and its application is flexible and easy.It is a new algorithm for assignment problem and it presents a new vision for other combinatorial optimization problems.

     

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