A decision support system for evaluating construction project recovery plans

Effective recovery planning is crucial for construction projects, known for their unpredictability and complexity. Current models for managing such projects often lack flexibility and real-time adaptability, leading to insufficient responsiveness to emerging challenges and disruptions. This paper presents a novel simulation-based Decision Support System (DSS) that integrates fuzzy logic and agent-based modeling (ABM) within an effects-based framework to evaluate recovery strategies. This DSS addresses the limitations of traditional project management tools by enabling project managers to simulate various strategies against multiple scenarios, thus aiding in making informed decisions. By blending the predictive power of fuzzy logic with the dynamic capabilities of ABM, the system provides a thorough analysis of project interdependencies and the impact of different strategies. Tested and validated on a $100 million real-world industrial project employing 280 personnel, the DSS has proven effective in improving resource allocation, minimizing project entropy, and enhancing predictability. This study underscores the value of combining expert knowledge with sophisticated simulation tools, offering managers a powerful resource for navigating project complexities and improving strategic planning, thus aiding project management and completion success.