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All Journal Bilangan: Jurnal Ilmiah Matematika, Kebumian dan Angkasa Algoritma: Jurnal Matematika, Ilmu Pengetahuan Alam, Kebumian dan Angkasa International Journal of Applied Mathematics and Computing.
Hasanain Hamed Ahmed
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Astronomy Computer Science & IT Earth & Planetary Sciences Mathematics

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Journal : International Journal of Applied Mathematics and Computing.

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Analyze The Effectiveness Of Dynamic Programming In Improving Robust Queue Management Strategies Hasanain Hamed Ahmed
International Journal of Applied Mathematics and Computing Vol. 1 No. 4 (2024): October: International Journal of Applied Mathematics and Computing
Publisher : Asosiasi Riset Ilmu Matematika dan Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/ijamc.v1i3.22

Abstract

This Article Review for aims to analyze the effectiveness of dynamic programming as a tool to improve robust queue management strategies in service systems. Dynamic programming is an optimization technique used to determine the optimal solution to problems that can be broken down into smaller problems. Explore how dynamic programming can be used to improve queue management strategies, including reducing wait times, improving resource allocation, and increasing system efficiency. The research is based on an analytical model that combines dynamic programming with row theory Immune-waiting, includes mathematical and experimental analysis to evaluate the effectiveness of these strategies in different applied contexts. The research aims to provide practical insights on how dynamic programming can be used to improve the performance of SOA systems and to provide recommendations for improving management strategies.
Using Mathematical Programming to Analyze and Improve Robust Queue Management in Healthcare Systems Hasanain Hamed Ahmed
International Journal of Applied Mathematics and Computing Vol. 2 No. 3 (2025): July : International Journal of Applied Mathematics and Computing
Publisher : Asosiasi Riset Ilmu Matematika dan Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/ijamc.v2i3.229

Abstract

Efficient management of patient queues is essential in healthcare systems to ensure timely care, optimize resource utilization, and enhance patient satisfaction. Mathematical programming, particularly when applied in conjunction with queuing theory and optimization models, provides a rigorous framework for analyzing and improving healthcare service delivery. This approach involves modeling arrivals and service processes, applying queuing models (such as single-server, multi-server, and priority queues), and formulating optimization objectives—often to minimize total costs, patient waiting times, or resource idling. Recent research demonstrates that combining queuing theory with mixed-integer programming and simulation techniques enables healthcare managers to allocate resources dynamically, set staffing levels, and assign priorities among different patient categories. For example, the use of mixed-integer programming can determine the optimal number of servers, beds, and service rates based on patient flow and priority needs, striking a balance between reducing waiting times for critical cases and controlling operational costs. These mathematical models also account for practical constraints and stochastic variability inherent in clinical settings. Applications span emergency departments, outpatient clinics, and even pharmacy and blood service centers—showing significant improvements in system efficiency, reduced patient wait times, and enhanced overall care quality. Thus, mathematical programming is a powerful decision-support tool for queue management, offering evidence-based strategies to address congestion and resource allocation challenges in complex healthcare environments.
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