The construction and infrastructure industry has witnessed an increase in the need for an optimized mitigation strategy to combat schedule and cost overruns amid the rise in market competitiveness and more strict timelines and budgets. Moreover, projects nowadays are more complex in terms their scope and requirements which ultimately drives more innovative and efficient solutions to enhance project risk mitigation. Typically, Monte Carlo (MC) simulations with different combinations of mitigation measures are performed until a random set of measures is chosen to satisfy the targeted budget. Several attempts aimed at optimizing around different objective functions to obtain more efficient strategies that would demonstrate the dynamics faced on the construction sites(Safaeian et al., 2022). The main flaw of all attempts were the absence of the goal-oriented control behavior of the project manager who would only opt to the optimal mitigation strategy given a risk event and cost overrun. The closest attempt was demonstrated in the objective functions of MitC developed to keep projects within schedule given a set of optimized mitigation strategies (Kammouh et al., 2021). However, the aforementioned tool solely addresses the selection of mitigation measures in the case of project delays affecting a strict delivery date with a trade-off restricted to one criterion: cost. The development in this document demonstrates a tool with broader functionalities that aims at selecting an optimized strategy to keep the project within budget yet with further additional features that extend its usefulness to a multi-criteria approach that involves time delays, environmental impacts as well as noise disturbance. The usefulness of the Mitigation controller for cost is demonstrated using a real case of a construction project in the Netherlands with the analysis performed on the go yielding significant negative impact savings relative to current approaches used to maintain the project’s budget.