Search Results - parallel optimization ((((scheduling algorithm) OR (system algorithm))) OR (bat algorithm))

A hybrid bat�swarm algorithm for optimizing dam and reservoir operation by Yaseen Z.M., Allawi M.F., Karami H., Ehteram M., Farzin S., Ahmed A.N., Koting S.B., Mohd N.S., Jaafar W.Z.B., Afan H.A., El-Shafie A.

A hybrid bat–swarm algorithm for optimizing dam and reservoir operation by Yaseen, Zaher Mundher, Allawi, Mohammed Falah, Karami, Hojat, Ehteram, Mohammad, Farzin, Saeed, Ahmed, Ali Najah, Koting, Suhana, Mohd, Nuruol Syuhadaa, Jaafar, Wan Zurina Wan, Afan, Haitham Abdulmohsin, El-Shafie, Ahmed

“…This study proposes a new hybrid optimization algorithm based on a bat algorithm (BA) and particle swarm optimization algorithm (PSOA) called the hybrid bat–swarm algorithm (HB-SA). …”
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Topology-aware hypergraph based approach to optimize scheduling of parallel applications onto distributed parallel architectures by Koohi, Sina Zangbari

“…Any optimization algorithm is suitable for only a specific domain of optimization problems. …”
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A hybrid genetic algorithm for optimization of scheduling workflow applications in heterogeneous computing systems by Ahmad, S.G., Liew, Chee Sun, Munir, E.U., Ang, Tan Fong, Khan, S.U.

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ROA-CONS: raccoon optimization job scheduling by Koohi, Sina Zangbari, Abdul Hamid, Nor Asilah Wati, Othman, Mohamed, Ibragimov, Gafurjan

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PID Parameters Improvement for AGC in Three Parallel-Connected Power Systems by Mushtaq, Najeeb, Ramdan, Razali, K. G., Mohammed, Hamdan, Daniyal, Ali, M. Humada

“…Integral Square Error (ISE) is considered as an objective function for both algorithms to determine its performance index value for the same parallel-connected power system. …”
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Web based personalized university timetable for UiTM students using genetic algorithm / Mohd Radhi Fauzan Jamli and Ahmad Firdaus Ahmad Fadzil by Jamli, Mohd Radhi Fauzan, Ahmad Fadzil, Ahmad Firdaus

“…Future work entails enhancing system robustness through comprehensive contingency planning, real-time data integration, and algorithmic optimization, with a focus on refining the genetic algorithm and exploring parallel processing techniques to further enhance efficiency and scalability.…”
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Quantum Particle Swarm Optimization Technique for Load Balancing in Cloud Computing by Elrasheed Ismail, Sultan

“…Load balancing optimization techniques such as Ant Colony Optimization (ACO), First Come First Served (FCFS), Round Robin (RR) and Particle Swarm Optimization (PSO) are popular techniques being used for scheduling and load balancing. …”
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A multi-layer perceptron for scheduling cellular manufacturing systems in the presence of unreliable machines and uncertain cost by Delgoshaei, Aidin, Gomes, Chandima

“…In this paper, a new method is proposed for short-term period scheduling of dynamic cellular manufacturing systems in the presence of bottleneck and parallel machines. …”
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Load-Balancing Models for Scheduling Divisible Load on Large Scale Data Grids by Abduh Kaid, Monir Abdullah

“…The IDLT model is capable of producing almost optimal solution for single source scheduling with low time complexity. …”
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Customised fitness function of evolutionary algorithm for optimization of car park space / Ahmad Syahir Ab. Aziz by Ab. Aziz, Ahmad Syahir

“…Genetic algorithm is chosen for the development of the prototype to prove that genetic algorithm is the best technique to implement for optimization. …”
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Optimization of extractive Automatic Text Summarization using Decomposition-based Multi-objective Differential Evolution and parallelization by Hazmi Wahab, Muhammad Hafizul

“…The central challenge in Automatic Text Summarization (ATS) is efficiently generating machine-generated text summaries through optimization algorithms, a critical component for systems dealing with textual information processing. …”
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OPTIMIZATION OF TWO FISH ENCRYPTION ALGORITHM ON FPGA by DORE RAJA, ANAND A RAJA

“…Besides that, Twofish also uses a 32 bit Pseudo Hadamard Transform to mix the outputs from its 2 parallel 32-bit g functions. Finally, Twofish needs a lot of key material, and has complicated key schedule. …”
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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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Simulated kalman filter (SKF) based image template matching for distance measurement by using stereo vision system by Nurnajmin Qasrina Ann, Ayop Azmi

“…After that, SKF is tested to find the most accurate image template matching and compared with Particle Swarm Optimization (PSO) and Bat Algorithm with Mutation (BAM). …”
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Deep Learning-Driven Mobility And Utility-Based Resource Management In Mm-Wave Enable Ultradense Heterogeneous Networks by Ukasyah bin Mahamod

Optimization Of Twofish Encryption Algorithm On FPGA by Raja, Ananda Raja Dore, Zain Ali, Noohul Basheer, Hussin, Fawnizu Azmadi

“…Besides that, Twofish also uses a 32 bit Pseudo Hadamard Transform to mix the outputs from its 2 parallel 32-bit g functions. Finally, Twofish needs a lot of key material, and has complicated key schedule. …”
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Development of appoinment scheduling agent using distributed constraint satisfaction (DisCS) by Mohd. Azmi, Nurulhuda Firdaus, Eri, Zeti Darleena, Ibrahim, Nuzulha Khilwani, Ahmad Rusli, Rozana Diana

“…The aim of this development is to optimize the reservation schedule towards efficiency schedule. …”
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Sequential and parallel multiple tabu search algorithm for multiobjective urban transit scheduling problems by Uvaraja, Vikneswary

“…Additionally, the MTS algorithm is also implemented in parallel computing to produce parallel MTS for generating comparable solutions in shorter computational times. …”
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Energy-aware task scheduling for streaming applications on NoC-based MPSoCs by Abd Ishak, Suhaimi Abd Ishak, Wu, Hui, Tariq, Umair Ullah

“…Our approach is supported by a set of novel techniques, which include constructing an initial schedule based on a list scheduling where the priority of each task is its approximate successor-tree-consistent deadline such that the workload across all the processors is balanced, a retiming heuristic to transform intraperiod dependencies into inter-period dependencies for enhancing parallelism, assigning an optimal discrete frequency for each task and each message using a Non-Linear Programming (NLP)-based algorithm and an Integer-Linear Programming (ILP)-based algorithm, and an incremental approach to reduce the memory usage of the retimed schedule in case of memory size violations. …”
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