A new genetic programming approach to dynamic multi-point dynamic aggregation problem

Created by W.Langdon from gp-bibliography.bib Revision:1.8855

@Article{Bi:2026:swevo,

• author = "Ying Bi and Xishui Xue and Ya-Hui Jia and Caitong Yue and Kai Zhang",
• title = "A new genetic programming approach to dynamic multi-point dynamic aggregation problem",
• journal = "Swarm and Evolutionary Computation",
• year = "2026",
• volume = "102",
• pages = "102339",
• keywords = "genetic algorithms, genetic programming, Multi-point dynamic aggregation, Real-time decision making, Hyper-heuristic",
• ISSN = "2210-6502",
• URL = "https://www.sciencedirect.com/science/article/pii/S2210650226000593",
• DOI = "10.1016/j.swevo.2026.102339",
• abstract = "... we propose a GP method with a new offspring selection method to enhance the diversity and convergence of the population, thereby improving the solution to the MPDA problem. Specifically, the number of offspring is increased by brood recombination, and then the offspring are divided into two subpopulations, where different selection strategies are developed. A niching selection strategy is proposed to reduce the complexity and to improve the diversity of the individuals. A K-nearest neighbor surrogate selection strategy is designed to improve the effectiveness. A self-adaptive scheme is designed to adjust the number of individuals selected from each subpopulation. The experimental results on various dynamic MPDA test sets show that the newly proposed algorithm significantly outperforms the traditional GP method and manually designed heuristics",
• notes = "Also known as \cite{BI2026102339}",

}

Genetic Programming entries for Ying Bi Xishui Xue Ya-Hui Jia Caitong Yue Kai Zhang

Citations