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为了解决大规模有资源约束的项目调度问题,提出一种串行分解和并行分解相结合的项目逐层分解方法,以便克服精确算法求解时间不可接受,而启发式算法解的质量较差的问题。根据该分解方法特点,提出基于采样选择的启发式协调方法,以及基于分枝定界方法的精确底层调度的子项目协调优化算法,并通过仿真分析了关键参数的选取。仿真结果表明,该算法解的平均质量明显优于相关启发式算法,并且求解时间能够满足工程上的要求,能够有效地提高大规模项目调度问题的求解质量,具有实用价值。
In order to solve the problem of large-scale resource-constrained project scheduling, a project-level decomposition method combining serial decomposition and parallel decomposition is proposed in order to overcome the problem of unacceptable solution time of accurate algorithm and poor quality of heuristic algorithm . According to the characteristics of this decomposition method, a heuristic coordination method based on sampling selection and a sub-project coordination and optimization algorithm based on branch-and-bound method are proposed, and the selection of key parameters is analyzed through simulation. The simulation results show that the average quality of the proposed algorithm is better than that of the relevant heuristic algorithm, and the solution time can meet the engineering requirements, which can effectively improve the quality of solving large-scale project scheduling problems, and has practical value.