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genetic algorithms » genetic algorithm (Expand Search)
coding algorithm » cosine algorithm (Expand Search), colony algorithm (Expand Search), scheduling algorithm (Expand Search)
implement » implemented (Expand Search), implementing (Expand Search)
element » elements (Expand Search)
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Implementation and Comparison of Particle Swarm Optimization and Genetic Algorithm Techniques in Combined Economic Emission Dispatch of an Independent Power Plant
Published 2019“…Two contemporary metaheuristic techniques, particle swarm optimization (PSO) and genetic algorithm (GA), have were simultaneously implemented for combined economic emission dispatch (CEED) of an independent power plant (IPP) situated in Pakistan for different load demands. …”
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Multi-Objective Optimisation of Injection Moulding Process for Dashboard Using Genetic Algorithm and Type-2 Fuzzy Neural Network
Published 2024“…Additionally, the multi-objective genetic algorithm (MOGA) was utilised to extract the most optimal parameters for the injection moulding process, aiming to minimise shear and residual stress and thereby increase the resistance of the final product. …”
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A New Parallel Genetic Algorithm Model
Published 2020“…This paper presents an implementation of three Genetic Algorithm models for solving a reliability optimization problem for a redundancy system with several failure modes, a modification on a parallel a genetic algorithm model and a new parallel genetic algorithm model. …”
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Allocating data to distributed-memory multiprocessors by genetic algorithms
Published 2016“…We present three genetic algorithms (GAs) for allocating irregular data sets to multiprocessors. …”
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A genetic algorithm for testable data path synthesis
Published 2017“…The approach is formulated as an allocation problem and solved using an efficient genetic algorithm that generates cost-effective testable designs. …”
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A new genetic algorithm approach for unit commitment
Published 1997“…This paper presents a new genetic algorithm approach to solve the unit commitment problem in electric power systems. …”
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An incremental approach for test scheduling and synthesis using genetic algorithms
Published 2017“…The method is based on a genetic algorithm that efficiently explores the testable design space. …”
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Concurrent BIST Synthesis and Test Scheduling Using Genetic Algorithms
Published 2007“…The method is based on a genetic algorithm that efficiently explores the testable design space and finds a sub-optimal test registers assignment for each k-test session. …”
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A method for the minimum coloring problem using genetic algorithms
Published 2006“…The algorithm was implemented and tested on various set of instances including large DIMACS challenge benchmark graphs, all yielding favorable results.…”
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A genetic-based algorithm for fuzzy unit commitment model
Published 2000“…The model takes the uncertainties in the forecasted load demand and the spinning reserve constraints in a fuzzy frame. The genetic algorithm (GA) approach is then used to solve the proposed fuzzy UCP model. …”
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Test case generation for path coverage. (c2000)
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Integrating genetic algorithms, tabu search, and simulatedannealing for the unit commitment problem
Published 1999“…A new implementation of the genetic algorithm is introduced. …”
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Nonlinear model predictive control of Hammerstein and Wiener modelsusing genetic algorithms
Published 2001“…In this paper a novel approach for the implementation of nonlinear MPC is proposed using genetic algorithms (GAs). …”
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Integrating Genetic Algorithms, Tabu Search, And Simulated Annealing For The Unit Commitment Problem
Published 2020“…A new implementation of the genetic algorithm is introduced. …”
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Genetic Algorithm Control Strategy for Heat Pump System in Battery Electric Buses
Published 2020“…This study proposes a genetic algorithm-based control strategy that optimizes the coefficient of performance of the HP system to decrease its energy consumption and maximize the driving range. …”
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Genetic Algorithm Analysis using the Graph Coloring Method for Solving the University Timetable Problem
Published 2018“…Genetic algorithms were successfully useful to solve many optimization problems including the university Timetable Problem. …”
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CNN and HEVC Video Coding Features for Static Video Summarization
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