Abstract
In this paper, the famous kernighan-Lin algorithm is adjusted and embedded into the simulated annealing algorithm and the genetic algorithm for continuous optimization problems. The performance of the different algorithms are evaluated using a set of well known optimization test functions.
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Nordli, T., Bouhmala, N. (2021). A Look-Ahead Based Meta-heuristics for Optimizing Continuous Optimization Problems. In: Pereira, A.I., et al. Optimization, Learning Algorithms and Applications. OL2A 2021. Communications in Computer and Information Science, vol 1488. Springer, Cham. https://doi.org/10.1007/978-3-030-91885-9_4
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DOI: https://doi.org/10.1007/978-3-030-91885-9_4
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