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Performance Analysis of Simulated Annealing and Genetic Algorithm on systems of linear equations
2021
F1000Research
Problem solving and modelling in traditional substitution methods at large scale for systems using sets of simultaneous equations is time consuming. For such large scale global-optimization problem, Simulated Annealing (SA) algorithm and Genetic Algorithm (GA) as meta-heuristics for random search technique perform faster. Therefore, this study applies the SA to solve the problem of linear equations and evaluates its performances against Genetic Algorithms (GAs), a population-based search
doi:10.12688/f1000research.73581.1
fatcat:ofr4qdawhfcipmxrvuil7twnie