Evolutionary Multi-Mode Slime Mould Optimization: A Hyper-Heuristic Algorithm Inspired by Slime Mould Foraging Behaviors-Reference-Cited by-同舟云学术

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Evolutionary Multi-Mode Slime Mould Optimization: A Hyper-Heuristic Algorithm Inspired by Slime Mould Foraging Behaviors

Published:2023-07-24 Issue: Volume:22 Page:2153-2160
ISSN:
Container-title:2023 Congress in Computer Science, Computer Engineering, & Applied Computing (CSCE)
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Author:

Zhong Rui¹,Zhang Enzhi¹,Munetomo Masaharu²

Affiliation:

1. Graduate School of Information Science and Technology, Hokkaido University,Sapporo,Japan

2. Hokkaido University,Information Initiative Center,Sapporo,Japan

Funder

JSPS KAKENHI

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10487132/10487174/10487305.pdf?arnumber=10487305

Reference44 articles.

1. Genetic algorithms

2. On the usage of differential evolution for function optimization

3. Particle swarm optimization

4. Slime mould algorithm: A new method for stochastic optimization

5. Material Generation Algorithm: A Novel Metaheuristic Algorithm for Optimization of Engineering Problems

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