Heterogeneous ant colony algorithm based on selective evolution mechanism and game strategy-Reference-Cited by-同舟云学术

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Heterogeneous ant colony algorithm based on selective evolution mechanism and game strategy

Published:2023-11-06 Issue: Volume: Page:
ISSN:0920-8542
Container-title:The Journal of Supercomputing
language:en
Short-container-title:J Supercomput

Author:

Wu Lisheng,You Xiaoming,Liu Sheng

Funder

National Natural Science Foundation of China

Shanghai Natural Science Foundation

Publisher

Springer Science and Business Media LLC

Subject

Hardware and Architecture,Information Systems,Theoretical Computer Science,Software

Link

https://link.springer.com/content/pdf/10.1007/s11227-023-05706-1.pdf

Reference55 articles.

1. Ezugwu AES, Adewumi AO, Frîncu ME (2017) Simulated annealing based symbiotic organisms search optimization algorithm for traveling salesman problem. Expert Syst Appl 77:189–210. https://doi.org/10.1016/j.eswa.2017.01.053

2. Emambocus BAS, Jasser MB, Hamzah M et al (2021) An Enhanced Swap Sequence-Based Particle Swarm Optimization Algorithm to Solve TSP. IEEE Access 9:164820–164836. https://doi.org/10.1109/ACCESS.2021.3133493

3. Dorigo M, Di Caro G, Gambardella LM (1999) Ant algorithms for discrete optimization. Artif Life 5:137–172. https://doi.org/10.1162/106454699568728

4. Liu S, Xiao Z, You X, Su R (2022) Multistrategy boosted multicolony whale virtual parallel optimization approaches. Knowledge-Based Syst 242:108341. https://doi.org/10.1016/j.knosys.2022.108341

5. Wang JJ, Wang J (2022) A cooperative memetic algorithm with feedback for the energy-aware distributed flow-shops with flexible assembly scheduling. Comput Ind Eng 168:108126. https://doi.org/10.1016/j.cie.2022.108126

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