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

Ying Bi

doi:10.1016/j.swevo.2026.102339

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

2026-02-24

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DOI：10.1016/j.swevo.2026.102339

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• A offspring selection strategy is proposed for genetic programming (GP). • A niching selection strategy is proposed to reduce the complexity of GP individuals. • A k-nearest neighbor surrogate selection strategy is adopted to enhance the convergence of the algorithm. • A self-adaptive mechanism is proposed to balance niching and surrogate selection.

Keywords:

genetic programming

niching selection

surrogate selection

dynamic multi-point aggregation

self-adaptive mechanism

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

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