Numerical results show that while the developed mathematical model works on small-scale problems, Lagrangian relaxation method finds better results for large scale scheduling problem with much smaller duality gap in a reasonable computational time.
📌 3 Key Takeaways
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Objective & Hypothesis:Öz The problem of nurse scheduling is categorized in a Np-Hard complexity as it is inherently composed of many limitations and assumptions.
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Key Findings & Data:As the number of nurses and the number of days increase, finding the solution of the problem becomes quite difficult.
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Conclusion & Impact:Numerical results show that while the developed mathematical model works on small-scale problems, Lagrangian relaxation method finds better results for large scale scheduling problem with much smaller duality gap in a reasonable computational time.
Öz The problem of nurse scheduling is categorized in a Np-Hard complexity as it is inherently composed of many limitations and assumptions. As the number of nurses and the number of days increase, finding the solution of the problem becomes quite difficult. Therefore, this paper propose both an integer-programming model and a Lagrangian relaxation approach for solving nurse-scheduling problem. Numerical results show that while the developed mathematical model works on small-scale problems, Lagrangian relaxation method finds better results for large scale scheduling problem with much smaller duality gap in a reasonable computational time.
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