Dynamic Programming Applications: A Suvrvey

Tarek, Amira; Elsayed, Hagar; Rashad, Manar; Hassan, M.R.; kafrawy, Passant el

doi:10.1109/niles50944.2020.9257968

Cited by 7 publications

(2 citation statements)

References 28 publications

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“…The amount of work that will be assigned to a server depends on that server's ability to process and the amount of data that can reach it [19]. For example, a server can handle 2 megabytes per second, but the amount of data flowing to it does not exceed one megabyte per second, this means that the server will operate at half its capacity, On the other hand, it cannot handle a data stream of more than 2 megabytes as a maximum.…”

Section: Proposed Ideamentioning

confidence: 99%

Dynamic Allocation of Weights Using the Minimally Connected Method to Augment Load Equilibrium in Distributed Systems

2024

IJIES

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Load balancing is critical to managing server resources efficiently and ensuring optimal performance in distributed systems. The weighted round robin (WRR) algorithm is commonly used to allocate incoming requests among servers based on their assigned weights. However, static weights may not reflect the changing demands of servers, leading to imbalanced workloads. To address this issue, this study proposes a dynamic mechanism for assigning weights to servers in the WRR algorithm based on the data rate and incorporates the least connection approach for the best result. The dynamic mechanism considers each server's real-time data rate, representing its current load. Servers with higher data rates are assigned higher weights to attract a larger share of incoming requests, while those with lower data rates receive lower weights to manage their loads effectively. This dynamic weight assignment allows the algorithm to adapt to varying workloads and achieve better load balancing across servers. To further refine the distribution of requests, the least connection approach is employed to handle tie-breaking situations and for more fairness in distributing the loads. The proposed algorithm is a hybrid of data rate and the least connection, it is evaluated through simulations and real-world experiments. The results demonstrate its superiority in achieving improved load balance compared to other algorithms, such as round-robin RR and traditional static-weight WRR algorithms. By dynamically adjusting weights based on data rate and employing the least connection approach, the algorithm optimizes server resource usage, minimizes response times, and enhances overall system performance in distributed environments.

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Section: Proposed Ideamentioning

confidence: 99%

Dynamic Allocation of Weights Using the Minimally Connected Method to Augment Load Equilibrium in Distributed Systems

2024

IJIES

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“…Dynamic programming has been applied in various contexts, like in project management (Choi et al 2004), remanufacturing (Li et al 2009), among other examples (La Torre et al 2019;Tarek et al 2020); its applications for production capacity planning are relatively limited (Choi et al 2006;Katanyukul et al 2011). From the existing studies, backlog (Kingsman 1997) and workload control (Kingsman 2000) were investigated as strategic dynamic capacity planning decisions.…”

Section: Introductionmentioning

confidence: 99%

Computationally efficient approximate dynamic programming for multi-site production capacity planning with uncertain demands

2022

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With globalization and rapid technological-economic development accelerating the market dynamics, consumers' demand is becoming more volatile and diverse. In this situation, capacity adjustment as an operational strategic decision plays a major role to ensure supply chain responsiveness while maintaining costs at a reasonable norm. This study contributes to the literature by developing computationally efficient approximate dynamic programming approaches for production capacity planning considering uncertainties and demand interdependence in a multi-factory multi-product supply chain setting. For this purpose, the k-Nearest-Neighbor-based Approximate Dynamic Programming (k-ADP) and the Rolling-Horizonbased Approximate Dynamic Programming (R-ADP) are developed to enable real-time decision support while ensuring the robustness of the outcomes in stochastic decision environments. Given the market volatilities in the Thin Film Transistor-Liquid Crystal Display (TFT-LCD) industry, a real case from this sector is investigated to evaluate the applicability of the developed approach and provide insights for other industry situations. The developed method is less complex to implement, and numerical experiments showed that it is also computationally more efficient compared to Stochastic Dynamic Programming (SDP).

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ATSA: An Adaptive Tree Seed Algorithm based on double-layer framework with tree migration and seed intelligent generation

Jiang,

Yang,

et al. 2023

Knowledge-Based Systems

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Dynamic Programming Applications: A Suvrvey

Cited by 7 publications

References 28 publications

Dynamic Allocation of Weights Using the Minimally Connected Method to Augment Load Equilibrium in Distributed Systems

Dynamic Allocation of Weights Using the Minimally Connected Method to Augment Load Equilibrium in Distributed Systems

Computationally efficient approximate dynamic programming for multi-site production capacity planning with uncertain demands

ATSA: An Adaptive Tree Seed Algorithm based on double-layer framework with tree migration and seed intelligent generation

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