Search Results - (( intelligence a scheduling algorithm ) OR ( intelligence based modeling algorithm ))

Hybrid ant colony system algorithm for static and dynamic job scheduling in grid computing by Alobaedy, Mustafa Muwafak Theab

“…The complexity of scheduling problem is considered as a nondeterministic polynomial complete (NP-complete) problem and therefore, an intelligent algorithm is required to achieve better scheduling solution. …”
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African Buffalo Optimization (ABO): A New Metaheuristic Algorithm by Odili, Julius Beneoluchi, M. N. M., Kahar

“…The African Buffalo Optimization (A.B.0) algorithm simulates the African buffalos' behaviour by encapsulation in a mathematical model; which solves a number of discrete optimization problems using graph-based route planning, job scheduling and it extends Swarm Intelligence paradigms. …”
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Application of an evolutionary algorithm-based ensemble model to job-shop scheduling by Tan, Choo Jun, Neoh, Siew Chin, Lim, Chee Peng, Hanoun, Samer, Wong, Wai Peng, Loo, Chu Kiong, Zhang, Li, Nahavandi, Saeid

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Optimization and control of hydro generation scheduling using hybrid firefly algorithm and particle swarm optimization techniques by Hammid, Ali Thaeer

“…To deal with these problems, this thesis introduces three approved intelligent controllers for hydropower generation. Firstly, a hybrid algorithm namely firefly particle swarm optimization (FPSO) and series division method (SDM) based on the practical swarm optimization and the firefly algorithm is proposed. …”
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Energy management scheduling for microgrids in the virtual power plant system using artificial neural networks by Abdolrasol M.G.M., Hannan M.A., Suhail Hussain S.M., Ustun T.S., Sarker M.R., Ker P.J.

Series division method based on PSO and FA to optimize Long-Term Hydro Generation Scheduling by Hammid, Ali Thaeer, M. H., Sulaiman

“…The SDM is to make a division on the Swarm Intelligence (SI) algorithm which is to be a number of particles searching collections that properly can be regarded as divisions. …”
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Enhancing Harmony Search Parameters Based On Step And Linear Function For Bus Driver Scheduling And Rostering Problems by Mansor, Nur Farraliza

“…Optimization is a major challenge in numerous practical world problems.According to the “No Free Lunch (NFL)” theorem,there is no existing single optimizer algorithm that is able to resolve all issues in an effective and efficient manner.It is varied and need to be solved according to the specific capabilities inherent to certain algorithms making it hard to foresee the algorithm that is best suited for each problem.As a result,the heuristic technique is adopted for this research as it has been identified as a potentially suitable algorithm.Alternative heuristic algorithms are also suggested to obtain optimal solutions with reasonable computational effort.However,the heuristic approach failed to produce a solution that nears optimum when the complexity of a problem increases;therefore a type of nature-inspired algorithm known as meta-euristics which utilises an intelligent searching mechanism over a population is considered and consequently used.The meta-heuristic approach is widely used to substitute heuristic terms and is broadly applied to address problems with regards to driver scheduling.However,this meta-heuristic technique is still unable to address the fairness issue in the scheduling and rostering problems.Hence,this research proposes a strategy to adopt an amendment of the harmony search algorithm in order to address the fairness issue which in turn will escalate the level of fairness in driver scheduling and rostering.The harmony search algorithm is classified as a meta-heuristics algorithm that is capable of solving hard and combinatorial or discrete optimisation problems.In this respect,the three main operators in harmony search,namely the Harmony Memory Consideration Rate (HMCR),Pitch Adjustment Rate (PAR) and Bandwidth (BW) play a vital role in balancing local exploitation and global exploration.These parameters influence the overall performance of the HS algorithm,and therefore it is crucial to fine-tune them. …”
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Dynamic traffic light sequence algorithm using RFID by Al-Khateeb, Khalid A. Saeed, Johari, Jaiz A. Y, Al-Khateeb, Wajdi Fawzi Mohammed

“…Results: The simulation has shown that, the dynamic sequence algorithm has the ability to intelligently adjust itself even with the presence of some extreme cases. …”
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A review on artificial intelligence based load demand forecasting techniques for smart grid and buildings by Raza, M.Q., Khosravi, A.

“…The major objective of this study is to review, identify, evaluate and analyze the performance of Artificial Intelligence (AI) based load forecast models and research gaps. …”
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Network calculus-based latency for time-triggered traffic under Flexible Window-Overlapping Scheduling (FWOS) in a Time-Sensitive Network (TSN) by Shalghum, Khaled M., Noordin, Nor Kamariah, Sali, Aduwati, Hashim, Fazirulhisyam

“…Accordingly, more relaxed scheduling algorithms are required. In this paper, we introduce the flexible window-overlapping scheduling (FWOS) algorithm that optimizes the overlapping among TT windows by three different metrics: the priority of overlapping, the position of overlapping, and the overlapping ratio (OR). …”
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Short-term electricity price forecasting in deregulated electricity market based on enhanced artificial intelligence techniques / Alireza Pourdaryaei by Alireza , Pourdaryaei

“…Finally, the obtained results corroborate the premise of the proposed method through the enhanced accuracy compared to the existing artificial intelligence-based models. …”
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Process Planning Optimization In Reconfigurable Manufacturing Systems by Musharavati, Farayi

“…The five (5) AADTs include; a variant of the simulated annealing algorithm that implements heuristic knowledge at critical decision points, two (2) cooperative search schemes based on a “loose hybridization” of the Boltzmann Machine algorithm with (i) simulated annealing, and (ii) genetic algorithm search techniques, and two (2) modified genetic algorithms. …”
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Processing time estimation in precision machining industry using AI / Lim Say Li by Lim, Say Li

“…Neural Network (NN) model is chosen as the artificial intelligence approach used in this research. …”
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Development of optimized maintenance scheduling model for coal-fired power plant boiler by Noor Fazreen Binti Ahmad Fuzi, Ms.

“…Computing intelligence is a soft-computing subset of artificial intelligence referring to the potential of a computer to gain knowledge from an experimental observations or specific task. …”

A New Grid Resource Discovery Framework by Mahamat Issa, Hassan, Azween , Abdullah

“…The paper integrates ontology, peer-to-peer (P2P) network and intelligent agents to build the framework. The framework consists of an ontology model, an agent model, and a set of algorithms for implementing the P2P architecture and searching the shared resources. …”
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Home Energy Management Systems: A Review of the Concept, Architecture, and Scheduling Strategies by Han B., Zahraoui Y., Mubin M., Mekhilef S., Seyedmahmoudian M., Stojcevski A.

“…In addition, the common objectives and constraints related to scheduling optimization are classified, and several optimization methods in the literature, including various intelligent algorithms, have been introduced, compared, and critically analyzed. …”

A New Grid Resource Discovery Framework by Hassan, Mahamat I., Azween, Abdullah

“…The paper integrates ontology, peer-to-peer (P2P) network and intelligent agents to build the framework. The framework consists of an ontology model, an agent model, and a set of algorithms for implementing the P2P architecture and searching the shared resources. …”
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A New Grid Resource Discovery Framework by Mahamat Issa, Hassan, Azween, Abdullah

“…The paper integrates ontology, peer-to-peer (P2P) network and intelligent agents to build the framework. The framework consists of an ontology model, an agent model, and a set of algorithms for implementing the P2P architecture and searching the shared resources. …”
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Optimization of operating cost and energy consumption in a smart grid by Mahdi, Baqer Saleh, Sulaiman, Nasri, Shehab, Mohanad Abd, Shafie, Suhaidi, Hizam, Hashim, Mohd Hassan, Siti Lailatul

“…The obtained results underscore the effectiveness and productivity of our devised NSGA-II-based approach. Notably, the proposed algorithm demonstrated a substantial reduction in electricity costs by 19.0%, peak-to-average ratio (PAR) by 30.7%, and carbon emissions by 21.7% in scenario-3, as evidenced by a comparative analysis with the unscheduled case.…”
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Application of nature-inspired algorithms and artificial intelligence for optimal efficiency of horizontal axis wind turbine / Md. Rasel Sarkar by Md. Rasel, Sarkar

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