System Engineering and Productivity

System Engineering and Productivity

An Integrated Multi-Objective Optimization Model for Risk-Interdependent Project Portfolio Selection and Scheduling under Resource Constraints

Document Type : Research Paper

Authors
Haniyeh Sadat Jebeli 1
Ali Namazian 2
1 M.Sc. Student, Department of Industrial Engineering, Faculty of Engineering, University of Kashan, Kashan, Iran
2 Corresponding author: Assistant Professor, Department of Industrial Engineering, Faculty of Engineering, University of Kashan, Kashan, Iran
10.22034/sep.2026.2086866.1477
Abstract
In highly competitive and uncertain environments, organizations are compelled to make simultaneous decisions regarding project selection and scheduling under resource constraints and exposure to complex risks. Many existing models in the literature consider project risks independently and overlook the networked interactions among them. However, in real-world settings, the occurrence of one risk may amplify the likelihood and severity of others. This study aims to develop a novel mathematical framework to support managers in selecting the optimal portfolio of projects and scheduling activities in a way that maximizes financial returns, minimizes overall completion time, and mitigates the adverse effects of interdependent risks. Accordingly, a multi-objective mixed-integer programming model is proposed for the integrated project portfolio selection and scheduling problem, incorporating risk networks and resource constraints. To model the dependencies among risks, a Bayesian network is employed, and the conditional probabilities of risks are embedded within the decision-making structure. Due to the nonlinear nature and computational complexity of the model, nonlinear relationships are first linearized. The model is then solved using a Genetic Algorithm combined with the Enhanced Epsilon-Constraint Method. Performance evaluation through numerical experiments at different scales demonstrates that the proposed approach can generate a diverse and high-quality Pareto frontier and plays an effective role in improving the trade-off among profit, project duration, and risk exposure.

Highlights

  • Simultaneous considering of project selection, project scheduling, and network-based risk effects under resource constraints.
  • Application of the multi-objective genetic algorithm NSGA-II to solve the proposed optimization problem.
  • Modeling interactions among dependent risks using a Bayesian network approach.

Keywords
Project Portfolio selection
Project Scheduling
Risk Network
Resource constraint
Multi-Objective Mathematical Model
Subjects

Copyright © Haniyeh Sadat Jebeli, Ali Namazian

 

License

This article is released under the Creative Commons Attribution (CC BY 4.0) license. Anyone is free to copy, share, translate, and adapt this article for any purpose, whether commercial or non-commercial, as long as proper citation is given to the authors and original publication.

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System Engineering and Productivity
Volume 6, Issue 4 - Serial Number 21
Winter 2027
Pages 281-312

  • Receive Date 27 February 2026
  • Revise Date 20 June 2026
  • Accept Date 10 July 2026
  • First Publish Date 18 July 2026
  • Publish Date 20 February 2027