Construction project management requires dynamic mitigation control to ensure a project's timely completion. Current mitigation approaches are usually performed by an iterative Monte Carlo (MC) analysis which does not reflect (1) the project manager's goal-oriented behavior, (2) contractual project completion performance schemes, and (3) stochastic dependence between construction activities. Therefore, the development statement within this paper is to design a method and implementation tool that properly dissolves all of the aforementioned shortcomings ensuring the project's completion date by finding the most effective and efficient mitigation strategy. For this purpose, the Mitigation Controller (MitC) has been developed using an integrative approach of nonlinear stochastic optimization techniques and probabilistic Monte Carlo analysis. MitC's applicability is demonstrated using a recent Dutch large infrastructure construction project showing its added value for dynamic control on-the-run. It is shown that the MitC is a state-of-the-art decision support tool that a-priori automates and optimizes the search for the best set of mitigation strategies on-the-run rather than a-posteriori evaluating the potentially sub-optimal and over-designed mitigation strategies (as commonly done with modern software such as Primavera P6).

建设项目管理需要动态缓解控制，以确保项目的及时完成。当前的缓解方法通常通过迭代蒙特卡罗 (MC) 分析来执行，该分析不反映 (1) 项目经理的目标导向行为，(2) 合同项目完成绩效计划，以及 (3) 施工活动之间的随机依赖性。因此，本文中的开发声明是设计一种方法和实施工具，通过找到最有效和最有效的缓解策略，适当地解决上述所有缺点，确保项目的完成日期。以此目的，缓解控制器 (MitC) 是使用非线性随机优化技术和概率蒙特卡罗分析的综合方法开发的。使用最近的荷兰大型基础设施建设项目证明了 MitC 的适用性，显示了其在运行中动态控制的附加值。结果表明，MitC 是一种最先进的决策支持工具，它先验自动化和优化在运行中寻找最佳缓解策略集，而不是后验评估潜在的次优和过度设计的缓解策略（通常使用 Primavera P6 等现代软件完成）。