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项目进度计划的鲁棒性对于不确定条件下项目的顺利实施具有重要影响.作者研究具有随机活动工期的资源约束项目鲁棒性调度问题,目标是在可更新资源和项目工期约束下安排活动的开始时间,以实现项目进度计划鲁棒性的最大化.首先对所研究问题进行界定并用一个示例对其进行说明.随后构建问题的优化模型,设计禁忌搜索、多重迭代和随机生成三种启发式算法.最后在随机生成的标准算例集合上对算法进行测试,分析项目活动数、项目工期和资源强度等参数对算法绩效的影响,并用一个算例对研究进行说明,得到如下结论:禁忌搜索的满意解质量明显高于其他两种算法;当资源强度或项目工期增大时,平均目标函数值上升,禁忌搜索的求解优势增强.研究结果可为不确定条件下项目进度计划的制定提供决策支持.
The robustness of the project schedule has an important impact on the successful implementation of the project under uncertain conditions. The authors study the problem of robust scheduling of resource-constrained projects with random active schedule, and the objective is to arrange activities under the constraints of renewable resources and project duration Start time to maximize the robustness of the project schedule.Firstly, define the problem and explain it with an example.Secondly, we build the optimization model of the problem, design tabu search, multiple iterations and random generation three heuristics Algorithm.Finally, the algorithm is tested on a randomly generated set of standard examples to analyze the impact of parameters such as project activity, project duration and resource intensity on the performance of the algorithm. An example is given to illustrate the research and the following conclusions are obtained: tabu search The quality of satisfactory solution is obviously higher than the other two algorithms.When the resource intensity or project duration increases, the average objective function value increases, and the tabu search results have more advantages.The research results can provide the decision-making for the project schedule under uncertain conditions stand by.