异构环境独立任务分配的导引式局部搜索算法

Guided Local Search Algorithm for Independent Tasks Assignment in Heterogeneous Environments

针对异构环境下的独立任务分配问题,结合变邻域下降算法,提出了一种导引式局部搜索算法.该算法通过不断动态修改原问题的目标函数和系统性地改变邻域结构,既保留了局部搜索算法的高效率,又能有效地避免陷入局部极小解,因而能够较快地得到满意解.与领域中的典型算法进行了仿真比较,结果表明提出的算法具有良好的性能.

A guided local search algorithm which is combined with variable neighborhood descent algorithm is presented to tackle the independent tasks assignment problem in heterogeneous environments. By dynamicaUy modifying the objective function and systematically changing the neighborhood structure, the algorithm can both keep the high efficiency of local search and overcome the shortage of getting stuck in local minimum, and thus it can obtain satisfactory solution quickly. The simulation results compared with typical algorithm in the fields show that the proposed algorithm produces good results.