Reducing the Impact of Bounded Parametric Uncertainty on Hodgson's Scheduling Algorithm Using Interval Programming

Hossny, Ahmad Hany; Creighton, Doug; Nahavandi, Saeid

doi:10.1109/jsyst.2015.2467184

Cited by 3 publications

(2 citation statements)

References 42 publications

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“…This algorithm provides improved results in terms of execution time and a utilization factor than the List, ECT, EST, LST, SPT scheduling algorithms. Utilization problems have been solved by minimizing the number of delayed tasks in a system with a single processor by applying EDD (Earliest Due Date First) rule on the task set T by Hodgson's scheduling algorithm [14]. Scheduled the unit length tasks based on precedence constraints in a system using Hu's scheduling algorithm [15].…”

Section: Avionic Mission System (Ams)mentioning

confidence: 99%

Boosted System Performance based on Execution Time Using LiMca Scheduling Algorithm

Sreenath¹,

Vijaya²

2021

JUSST

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The scheduling algorithms have been examined by the process of task execution in a system to achieve maximum utilization of multiprocessors. Consequently, the research attempted to propose a new real-time scheduling algorithm to support a multiprocessor platform. The proposed scheduling algorithm, List Mcnaughton’s amalgamation (LiMca) scheduling algorithm has been developed for an optimum solution with the features of List and Mcnaughton’s scheduling algorithms to overcome the individual drawbacks (pre-emption and Precedence constraints). In LiMca, Workload has been distributed to the processors in a system by sorting the tasks in decreasing order with their precedence constraints including due dates, pre-emption, and context switching. In this arena, the LiMca scheduling algorithm has been developed on a traditional avionic mission system and also simulated on a real-time application. The extensive simulations were carried out on the time optimization of resources scheduling (TORSCHE) simulation toolbox. LiMca scheduling algorithm performed superior as compared to recently reported scheduling algorithms like list, hu’s, McNaughton’s, Brucker’s, and Hodgson’s in terms of computational performance.

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Section: Avionic Mission System (Ams)mentioning

confidence: 99%

Boosted System Performance based on Execution Time Using LiMca Scheduling Algorithm

Sreenath¹,

Vijaya²

2021

JUSST

View full text Add to dashboard Cite

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“…The ability to handle the uncertainty associated with unstructured environments is a key element for succeeding on this. Handling uncertainty in scheduling related problems has been solved based on mathematical models, by employing probability theory [5], [6], numerical analysis [7], and interval mathematics [8], [9]. However, most real-world problems are too complex to be modelled mathematically.…”

Section: Introductionmentioning

confidence: 99%

Enabling Field Force Operational Sustainability: A Big Bang-Big Crunch Type-2 Fuzzy Logic System for Goal-Driven Simulation

Ferreyra

Hagras

Kern

et al. 2018

2018 IEEE Symposium Series on Computational Intelligence (SSCI)

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Business operational sustainability must allow creating economic value, building healthy ecosystems and developing strong communities. Hence, there is a need to develop solutions which can safeguard companies' business sustainability. Various solutions could have different costs and deliver different benefits. Therefore, there is a need to evaluate these solutions before being implemented. In reality, companies require achieving certain targets according to their plans and strategies. Goal-Driven Simulation (GDS) is an approach that allows evaluating solutions before implementing them in real-life while focusing on achieving desired targets. This paper presents a GDS based on interval type-2 Fuzzy Logic System (IT2FLS) optimized by the big bang-big crunch (BB-BC) algorithm with application to field force allocation within the telecommunications sector. The obtained results show the suitability of the proposed approach to model unexpected factors to protect the business sustainability in the telecommunications industry field force allocation domain.

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A type-2 fuzzy logic system for engineers estimation in the workforce allocation domain

Ferreyra

Hagras

Mohamed

et al. 2017

2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)

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Reducing the Impact of Bounded Parametric Uncertainty on Hodgson's Scheduling Algorithm Using Interval Programming

Cited by 3 publications

References 42 publications

Boosted System Performance based on Execution Time Using LiMca Scheduling Algorithm

Boosted System Performance based on Execution Time Using LiMca Scheduling Algorithm

Enabling Field Force Operational Sustainability: A Big Bang-Big Crunch Type-2 Fuzzy Logic System for Goal-Driven Simulation

A type-2 fuzzy logic system for engineers estimation in the workforce allocation domain

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