Algorithms and Optimization for Project Management and Supply Chain Management

Dear Colleagues,

It is my pleasure to invite you to submit your cutting-edge and contemporary research on optimization algorithms to solve different operation management problems. The key application areas of this Special Issue are project management and supply chain management. Fundamentally, project scheduling has been considered one of the critical tasks in project management, which predominantly assumes scheduling project activities by satisfying precedence and resource constraints. By virtue of proper project scheduling, a project manager can determine the timeline, allocate resources, plan for the budget, and most importantly get a sense of the reality of delivering the project (Chakrabortty et al., 2019). Nevertheless, due to the COVID-19 pandemic and its subsequent impacts, traditional project management and scheduling are now characterized by volatility, uncertainty, complexity, and ambiguity. Thus, to sustain a nation’s economic growth and competitiveness in the new reality, it is vital not to cancel but to optimize affected or vulnerable project portfolios (Chakrabortty and Ryan, 2020).

To do so, embedding business reforms, accelerating the digital transformation of classical projects, and implementing advanced technologies and automation programs (e.g., artificial intelligence-based approaches) in supply chain and project management problems can encourage better business agility, which is potentially a shortcoming in the available literature (Rahman et al., 2021). Moreover, in practice, while scheduling activities for multiple projects in dynamic environments, project managers face challenges typically due to the lack of timely, accurate, and consistent information; finite resource transfer times and interdependencies among activities of different projects; and uncertain activity interruptions. Therefore, to avoid these issues, an integrated framework considering both project management features and supply chain drivers, advanced solution approaches, and better ways of dealing with uncertainties (e.g., artificial-intelligence-based) can lead to an optimal decision support system for the whole business.

This Special Issue aims to bring together optimization algorithms to optimize supply chain drivers (e.g., supplier selection, make or buy decision, subcontracting or overtime option, project compression or project crashing, inventory handling, number of orders, lead times, supply uncertainty, lead time uncertainty, product availability) while simultaneously managing projects.

References

CHAKRABORTTY, R., ABBASI, A. & RYAN, M. J. 2019. A risk assessment framework for scheduling projects with resource and duration uncertainties. IEEE Transactions on Engineering Management.

CHAKRABORTTY, R. K. & RYAN, M. J. Robust Optimization Based Heuristic Approach for Solving Stochastic Multi-Mode Resource Constrained Project Scheduling Problem.  2020 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM), 2020. IEEE, 1157-1161.

RAHMAN, H. F., CHAKRABORTTY, R. K., ELSAWAH, S. & RYAN, M. J. 2021. Energy-Efficient Project Scheduling with Supplier Selection in Manufacturing Projects. Expert Systems with Applications, 116446.

Dr. Ripon Kumar Chakrabortty
Guest Editor

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