Journal of Industrial Engineering Research in  Production Systems

Journal of Industrial Engineering Research in Production Systems

Vulnerability Analysis of Activities and a Two-Stage Approach for Stochastic Multi-Mode Resource-Constrained Project Scheduling

Document Type : Research Paper

Authors
1 Department of Industrial Engineering, Faculty of Industrial and Systems Engineering, Tarbiat Modares University, Tehran, Iran
2 Department of Industrial Engineering, Faculty of Engineering, Bu-Ali Sina University, Hamedan, Iran
Abstract
Projects are inherently subject to various uncertainties and disruptions, which are among the main causes of project completion delays and reduced reliability of the initial schedule. However, in real-world project environments, activities are not equally affected by disruptions, and ignoring these differences can lead to inefficient resource allocation and unnecessary cost overruns. This study proposes a novel approach to assessing activity vulnerability and vulnerability-based resource acquisition in the multi-mode resource-constrained project scheduling problem with stochastic activity durations. In the first stage, 11 network-based, temporal, and resource-based indicators are extracted and weighted using the Shannon entropy method. The vulnerability level of each activity is then calculated as a weighted combination of these indicators. Based on this, a heuristic algorithm is developed to acquire renewable resources, prioritizing activities with higher vulnerability and determining the purchase quantity as a function of the vulnerability index, resource tightness, and maximum resource requirement. Once the purchase quantities are determined, the proposed mixed-integer linear programming (MILP) model is solved to make scheduling and resource allocation decisions under uncertainty. Computational results show that the vulnerability-based resource acquisition strategy reduces makespan compared to no acquisition, while the two-stage heuristic-exact approach significantly reduces computational time compared to solving the MILP model directly. These findings highlight that identifying vulnerable activities plays a key role in enhancing the robustness of project scheduling.
Keywords

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