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Ant colony optimization with self-adaptive evaporation rate in dynamic environments.

, and . CIDUE, page 47-54. IEEE, (2014)

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Evolving neural networks using ant colony optimization with pheromone trail limits., and . UKCI, page 16-23. IEEE, (2013)Evolutionary Computation for Dynamic Optimization Problems.. GECCO (Companion), page 629-649. ACM, (2015)An adaptation reference-point-based multiobjective evolutionary algorithm., , , , , , and . Inf. Sci., (2019)Dynamic Optimization Using Analytic and Evolutionary Approaches: A Comparative Review., and . Handbook of Optimization, volume 38 of Intelligent Systems Reference Library, Springer, (2013)Genetic Algorithms with Elitism-Based Immigrants for Changing Optimization Problems.. EvoWorkshops, volume 4448 of Lecture Notes in Computer Science, page 627-636. Springer, (2007)Associative Memory Scheme for Genetic Algorithms in Dynamic Environments.. EvoWorkshops, volume 3907 of Lecture Notes in Computer Science, page 788-799. Springer, (2006)A Guided Search Non-dominated Sorting Genetic Algorithm for the Multi-Objective University Course Timetabling Problem., and . EvoCOP, volume 6622 of Lecture Notes in Computer Science, page 1-13. Springer, (2011)Adapting the Pheromone Evaporation Rate in Dynamic Routing Problems., and . EvoApplications, volume 7835 of Lecture Notes in Computer Science, page 606-615. Springer, (2013)Dynamic Feature Selection for Clustering High Dimensional Data Streams., and . IEEE Access, (2019)A feedback-based prediction strategy for dynamic multi-objective evolutionary optimization., , , , and . Expert Syst. Appl., (2021)