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Simulated Annealing is a Polynomial-Time Approximation Scheme for the Minimum Spanning Tree Problem.

, , and . Algorithmica, 86 (1): 64-89 (January 2024)

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Escaping Local Optima with Local Search: A Theory-Driven Discussion., , , and . PPSN (2), volume 13399 of Lecture Notes in Computer Science, page 442-455. Springer, (2022)Stagnation detection in highly multimodal fitness landscapes., and . GECCO, page 1178-1186. ACM, (2021)Stagnation Detection Meets Fast Mutation., and . EvoCOP, volume 13222 of Lecture Notes in Computer Science, page 191-207. Springer, (2022)Stagnation Detection with Randomized Local Search., and . Evol. Comput., 31 (1): 1-29 (Spring 2023)Self-Adjusting Evolutionary Algorithms for Multimodal Optimization., and . Algorithmica, 84 (6): 1694-1723 (2022)Stagnation Detection with Randomized Local Search., and . EvoCOP, volume 12692 of Lecture Notes in Computer Science, page 152-168. Springer, (2021)Self-adjusting evolutionary algorithms for multimodal optimization., and . GECCO, page 1314-1322. ACM, (2020)Simulated Annealing is a Polynomial-Time Approximation Scheme for the Minimum Spanning Tree Problem., , and . Algorithmica, 86 (1): 64-89 (January 2024)Stagnation detection meets fast mutation., and . Theor. Comput. Sci., (February 2023)Simulated annealing is a polynomial-time approximation scheme for the minimum spanning tree problem., , and . GECCO, page 1381-1389. ACM, (2022)