Search Results - (( parallel solution using algorithm ) OR ( parameter optimization _ algorithm ))
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Application Of Genetic Algorithms For Robust Parameter Optimization
Published 2010“…Such a mechanism has a parallel application in parameter optimization. Factors in a parameter design can be expressed as a genetic analogue in a pool of sub-optimal random solutions. …”
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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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Intelligent classification algorithms in enhancing the performance of support vector machine
Published 2019“…The difference between the algorithms is the size of the solution archive. The size of the archive in ACOMV is fixed while in IACOMV, the size of solution archive increases as the optimization procedure progress. …”
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A hybrid bat–swarm algorithm for optimizing dam and reservoir operation
Published 2019“…Recently, evolutionary algorithms (EA) are used to develop optimal operation rules for dam and reservoir water systems. …”
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Development of optimization Alghorithm for uncertain non-linear dynamical system
Published 2004“…An algorithm that definitely can satisfy the objectives is the Dynamic Integrated Systems Optimization and Parameter Estimation (DISOPE) algorithm. …”
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Monograph -
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Single and Multiple variables control using Tree Physiology Optimization
Published 2017“…The proposed algorithm is also compared with deterministic gradient-free algorithm: Nelder-Mead simplex (NMS) and another metaheuristic algorithm: Particle Swarm Optimization (PSO). …”
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Web based personalized university timetable for UiTM students using genetic algorithm / Mohd Radhi Fauzan Jamli and Ahmad Firdaus Ahmad Fadzil
Published 2024“…This configuration excelled in efficiency and scalability, offering a viable solution for timetable generation at scale. 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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Multi-objectives process optimization in end milling process of aluminium alloy 6061-T6 using genetic algorithm
Published 2024“…However, only a final solution was selected according to the multi-objective optimization of each insert used in the experiments. …”
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Analysis of parallel flow type internally cooled membrane-based liquid desiccant dehumidifier using a neural networks approach
Published 2021“…The reverse modeling prediction will aid in dynamically adjusting the operating parameters to achieve the optimal thermodynamic output characteristics.…”
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Hyper-heuristic approaches for data stream-based iIntrusion detection in the Internet of Things
Published 2022“…Hence, the algorithm must overcome the problem of dynamic updates in the internal parameters or counter the concept drift. …”
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Thesis -
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Development of a multi-objective optimization model for transport and environment in a closed-loop automotive supply chain
Published 2014“…In the last stage, an extended Gravitational Search Algorithm (GSA) as a parallel search algorithm and high convergence rate into high quality final solutions is used to solve the proposed mathematical model and to achieve the Pareto set of solution. …”
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Analysis of Shrinkage on Thick Plate Part using Genetic Algorithm
Published 2016“…This paper presents a systematic methodology to analyse the shrinkage of the thick plate part during the injection moulding process. Genetic Algorithm (GA) method was proposed to optimise the process parameters that would result in optimal solutions of optimisation goals. …”
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A Dual Recurrent Neural Network-based Hybrid Approach for Solving Convex Quadratic Bi-Level Programming Problem
Published 2020“…Subsequently, in the lower-level, the parameterized-DRNN is used to determine possible optimal solutions. This combination offers several benefits such as being a parallel computing structure, the RNN offers faster convergence to the optimum for the lower-level decision problem and it also helps to quickly and accurately determining the global optimal. …”
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Deep Learning-Driven Mobility And Utility-Based Resource Management In Mm-Wave Enable Ultradense Heterogeneous Networks
Published 2025thesis::doctoral thesis -
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Parallel metaheuristic algorithm for route planning using CUDA
Published 2025“…This research will be focusing on developing a Parallel Metaheuristic Algorithm for Route Planning using CUDA to improve the efficiency and performance of route planning. …”
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Parallel Homologous Search With Hirschberg Algorithm: A Hybrid MPI-Pthreads Solution.
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Fast Finite Difference Time Domain Algorithms for Solving Antenna Application Problem
Published 2008“…Results show that these new sequential and parallel algorithms run faster than the standard sequential and parallel FDTD algorithms. …”
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Parallel block methods for solving higher order ordinary differential equations directly
Published 1999“…A new parallel algorithm for solving systems of ODEs using variable step size and order is also developed. …”
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A new method for decreasing cell-load variation in dynamic cellular manufacturing systems
Published 2016“…The Taguchi method (an L_9 orthogonal optimization) is used to estimate parameters of GA in order to solve experiments derived from literature. …”
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