An ensemble algorithm with self-adaptive learning techniques for high-dimensional numerical optimization

DOI10.1016/j.amc.2013.12.130zbMath1410.90282OpenAlexW1985217255MaRDI QIDQ1644541

Shuiming Zhong, Bin Xu, Yu Xue, Yi Zhuang

Publication date: 21 June 2018

Published in: Applied Mathematics and Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.amc.2013.12.130

zbMATH Keywords

evolutionary algorithmnumerical optimizationhigh-dimensionalensembleself-adaptation

Mathematics Subject Classification ID

Numerical mathematical programming methods (65K05) Approximation methods and heuristics in mathematical programming (90C59)

Related Items (1)

Evolving interpretable decision trees for reinforcement learning

Uses Software

• Hyperheuristics

Cites Work

• Evolutionary optimization: pitfalls and booby traps
• Self-adaptive learning based particle swarm optimization
• An ensemble of discrete differential evolution algorithms for solving the generalized traveling salesman problem
• Large scale evolutionary optimization using cooperative coevolution
• New mutation schemes for differential evolution algorithm and their application to the optimization of directional over-current relay settings
• Improved immune algorithm for global numerical optimization and job-shop scheduling problems
• A novel hybrid discrete differential evolution algorithm for blocking flow shop scheduling problems
• Differential evolution -- a simple and efficient heuristic for global optimization over continuous spaces
• Global and local real-coded genetic algorithms based on parent-centric crossover operators
• Exploring Hyper-heuristic Methodologies with Genetic Programming

This page was built for publication: An ensemble algorithm with self-adaptive learning techniques for high-dimensional numerical optimization