Scopus İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/395
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Article Citation - WoS: 2Citation - Scopus: 2Project Management in a Competitive Environment: Interdicting a CPM Based Project and Its Implications(Edp Sciences S A, 2021) Kasimoglu, Fatih; Akgun, IbrahimThere are two opponents in a classic network interdiction problem, network owner/defender and interdictor/attacker. Each side has enough information about the other's possible courses of action. While the network user wishes to run the network in an optimal way, the attacker with the limited resources tries to prevent the optimal operation of the network by interdicting the arcs/nodes of the network. In this study, we investigate project management in a competitive environment using a network interdiction approach. We assume that the project owner/manager strives to minimize the completion time of a Critical Path Method (CPM) based project while an opponent attempts to maximize the minimum completion time by inflicting some delays on project activities with available interdiction resources. Considering both discrete and continuous delay times, we develop two bi-level mixed-integer programming models for the interdictor. Using duality, we then convert the bi-level models to standard single-level models, which are solvable through standard optimization packages. We extend these models to find efficient solutions in terms of project completion time and interdiction resources from the interdictor's perspective. In this respect, we develop an algorithm to find an efficient solution set for the interdictor. Next, from project manager's standpoint, we discuss the earliest and latest scheduling times of activities in case of interdiction. Finally, we apply the developed techniques in a marketing project aiming at introducing a new product. The findings may enhance a better project management in an environment where an opponent can adversely affect the project management process by delaying some activities.Article Citation - WoS: 29Citation - Scopus: 31A Simulation-Based Approximate Dynamic Programming Approach to Dynamic and Stochastic Resource-Constrained Multi-Project Scheduling Problem(Elsevier, 2024) Satic, U.; Jacko, P.; Kirkbride, C.We consider the dynamic and stochastic resource -constrained multi -project scheduling problem which allows for the random arrival of projects and stochastic task durations. Completing projects generates rewards, which are reduced by a tardiness cost in the case of late completion. Multiple types of resource are available, and projects consume different amounts of these resources when under processing. The problem is modelled as an infinite -horizon discrete -time Markov decision process and seeks to maximise the expected discounted long -run profit. We use an approximate dynamic programming algorithm (ADP) with a linear approximation model which can be used for online decision making. Our approximation model uses project elements that are easily accessible by a decision -maker, with the model coefficients obtained offline via a combination of Monte Carlo simulation and least squares estimation. Our numerical study shows that ADP often statistically significantly outperforms the optimal reactive baseline algorithm (ORBA). In experiments on smaller problems however, both typically perform suboptimally compared to the optimal scheduler obtained by stochastic dynamic programming. ADP has an advantage over ORBA and dynamic programming in that ADP can be applied to larger problems. We also show that ADP generally produces statistically significantly higher profits than common algorithms used in practice, such as a rule -based algorithm and a reactive genetic algorithm.