A reinforcement learning-based neighborhood search operator for multi-modal optimization and its applications-Reference-Cited by-同舟云学术

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A reinforcement learning-based neighborhood search operator for multi-modal optimization and its applications

Published:2024-07 Issue: Volume:246 Page:123150
ISSN:0957-4174
Container-title:Expert Systems with Applications
language:en
Short-container-title:Expert Systems with Applications

Author:

Hong Jiale^ORCID,Shen Bo^ORCID,Pan Anqi^ORCID

Publisher

Elsevier BV

Reference48 articles.

1. Differential evolution using a neighborhood-based mutation operator;Das;IEEE Transactions on Evolutionary Computation,2009

2. A meta-heuristic proposal for inverse kinematics solution of 7-DOF serial robotic manipulator: quantum behaved particle swarm algorithm;Dereli;Artificial Intelligence Review,2020

3. A new effective operator for the hybrid algorithm for solving global optimisation problems;Duc;International Journal of Systems Science,2018

4. Eberhart, R., & Kenned, J. (1995). A new optimizer using particle swarm theory. In Proceedings of the sixth international symposium on micro machine and human science (pp. 39–43).

5. A comparative study of soft computing methods to solve inverse kinematics problem;El-Sherbiny;Ain Shams Engineering Journal,2018

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Dynamic Niches-Based Hybrid Breeding Optimization Algorithm for Solving Multi-Modal Optimization Problem;Mathematics;2024-09-08

2. A self-adaptive agent for flexible posture planning in robotic milling system;Journal of Manufacturing Systems;2024-08

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