An Integrated Framework for Risk Response Planning Under Resource Constraints in Large Engineering Projects

Abstract

Engineering project managers often face a challenge to allocate tight resources for managing interdependent risks. In this paper, a quantitative framework of analysis for supporting decision making in project risk response planning is developed and studied. The design structure matrix representation is used to capture risk interactions and build a risk propagation model for predicting the global mitigation effects of risk response actions. For exemplification, a genetic algorithm is used as a tool for choosing response actions and allocating budget reserves. An application to a real transportation construction project is also presented. Comparison with a sequential forward selection greedy algorithm shows the superiority of the genetic algorithm search for optimal solutions, and its flexibility for balancing mitigation effects and required budget.