Search Results - (( parallel optimization _ algorithm ) OR ( program optimization based algorithm ))
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Investigation on the dynamic of computation of semi autonomous evolutionary computation for syntactic optimization of a set of programming codes
Published 2007“…In parallel programming, the challenges in optimizing the codes in general are more than that for serial programming. …”
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Research Report -
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Topology-aware hypergraph based approach to optimize scheduling of parallel applications onto distributed parallel architectures
Published 2020“…Any optimization algorithm is suitable for only a specific domain of optimization problems. …”
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3
Application of intelligence based genetic algorithm for job sequencing problem on parallel mixed-model assembly line
Published 2010“…This study presented an intelligence based genetic algorithm approach to optimize the considered problem objectives through reducing the problem complexity. …”
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Article -
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Parallel distributed genetic algorithm development based on microcontrollers framework
Published 2023“…Genetic algorithms are powerful optimizing techniques that are used successfully to solve problems in many different disciplines. …”
Conference paper -
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Sequential and parallel multiple tabu search algorithm for multiobjective urban transit scheduling problems
Published 2018“…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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6
Web based personalized university timetable for UiTM students using genetic algorithm / Mohd Radhi Fauzan Jamli and Ahmad Firdaus Ahmad Fadzil
Published 2024“…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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Restoration planning strategy of transmission system based on optimal energizing time of sectionalizing islands / Dian Najihah Abu Talib
Published 2019“…There are two discrete optimization techniques used in this work, which are the Artificial Bee Colony algorithm and Evolutionary Programming. …”
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8
A Dual Recurrent Neural Network-based Hybrid Approach for Solving Convex Quadratic Bi-Level Programming Problem
Published 2020“…The current paper presents a neural network-based hybrid strategy that combines a Genetic Algorithm (GA) and a Dual Recurrent Neural Network (DRNN) for efficiently and accurately solving the quadratic-Bi-level Programming Problem (BLPP). …”
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Evaluation of Image Pixels Similarity Measurement Algorithm Accelerated on GPU with OpenACC
Published 2017“…OpenACC is a directive based parallel programming library that allows for easy acceleration of existing C, C++ and Fortran based applications with minimal code modifications. …”
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Two-stage strategic optimal planning of distributed generators and energy storage systems considering demand response program and network reconfiguration
Published 2025“…The Non-dominated Sorting Genetic Algorithm II (NSGA-II) is utilized to address the outer-stage optimization problem. …”
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Load-Balancing Models for Scheduling Divisible Load on Large Scale Data Grids
Published 2009“…There are some scheduling models, which have been studied, such as Constraint DLT (CDLT), Task Data Present (TDP) and Genetic Algorithm (GA). However, there has been no optimal solution reached. …”
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12
Speech compression using compressive sensing on a multicore system
Published 2011“…Finally, to speed up the process, the proposed algorithm will be implemented in a multicore system, i.e. six cores, using Single Program Multiple Data (SPMD) parallel paradigm.…”
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Proceeding Paper -
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Energy-aware task scheduling for streaming applications on NoC-based MPSoCs
Published 2024“…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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Numerical methods for nonlinear optimal control problems using haar wavelet operational matrices / Waleeda Swaidan Ali
Published 2015“…This thesis is based on solving optimal control problems by using both direct and indirect methods. …”
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Scheduling dynamic cellular manufacturing systems in the presence of cost uncertainty using heuristic method
Published 2016“…Since the proposed models (like similar models in the literature) are likely to fall into local optimum points, a Branch and Bound based heuristic, a hybrid Simulated Annealing and Genetic algorithm, a hybrid Tabu search and Simulated Annealing, a hybrid Genetic algorithm and Simulated Annealing, a hybrid Ant Colony Optimization and Simulated Annealing and a hybrid Multi-layer Perceptron and Simulated Annealing algorithms are developed. …”
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Parallel metaheuristic algorithm for route planning using CUDA
Published 2025“…Area of Study: Massively Parallel Computing, Combinatorial Optimization Keywords: Parallel Metaheuristic Algorithm, Travelling Salesman Problem, CUDA, GPU, Genetic Algorithm…”
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Final Year Project / Dissertation / Thesis -
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DC-based PV-powered home energy system
Published 2017“…A controller based on an algorithm of one time maximum power point (MPP) is proposed to mitigate those losses. …”
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Performance Comparison of Parallel Bees Algorithm on Rosenbrock Function
Published 2012“…This thesis presents the parallel Bees Algorithm as a new approach for optimizing the last results for the Bees Algorithm. …”
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Voting algorithms for large scale fault-tolerant systems
Published 2011“…To solve this problem and gain benefits of this algorithm, we employed parallel algorithm technique and by using optimal number of processors, we could propose optimal algorithms known as Parallel Average Voting and Parallel Weighted Average Voting which both have optimal time complexity and less calculation cost. …”
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