An improved ant colony optimization with an automatic updating mechanism for constraint satisfaction problems-Reference-Cited by-同舟云学术

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An improved ant colony optimization with an automatic updating mechanism for constraint satisfaction problems

Published:2021-02 Issue: Volume:164 Page:114021
ISSN:0957-4174
Container-title:Expert Systems with Applications
language:en
Short-container-title:Expert Systems with Applications

Author:

Guan Boxin,Zhao Yuhai,Li Yuan

Funder

National Natural Science Foundations of China

Project of Beijing Municipal Education Commission

North China University of Technology

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Science Applications,General Engineering

Reference34 articles.

1. Aratsu, Y., Mizuno, K., Sasaki, H., & Nishihara, S. Experimental evaluation of artificial bee colony with greedy scouts for constraint satisfaction problems. 2013 Conference on Technologies and Applications of Artificial Intelligence (pp. 134–139).

2. Bidar, M. & Mouhoub, M. (2019a). Solving weighted constraint satisfaction problems using a new self-adaptive discrete firefly algorithm. 2019 IEEE International Conference on Systems, Man and Cybernetics (SMC) (pp. 2198–2205).

3. Bidar, M. & Mouhoub, M. (2019b). Discrete particle swarm optimization algorithm for dynamic constraint satisfaction with minimal perturbation. 2019 IEEE International Conference on Systems, Man and Cybernetics (SMC).

4. Bit-Monnot, A. (2018). A constraint-based encoding for domain-independent temporal planning. International Conference on Principles and Practice of Constraint Programming (pp. 229–241).

5. Discrete temporal constraint satisfaction problems;Bodirsky;Journal of the ACM,2018

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