A framework for multi-objective optimization of virtual tree pruning based on growth simulation

作者：

Highlights：

• A framework for multi-objective optimization of virtual tree pruning is presented.

• Tree growth simulation is used to evaluate the long-term effects of pruning.

• The case study uses light intake of pruned trees as pruning objectives.

• NSGA-II builds better non-dominated solution sets than local search heuristic.

摘要

•A framework for multi-objective optimization of virtual tree pruning is presented.•Tree growth simulation is used to evaluate the long-term effects of pruning.•The case study uses light intake of pruned trees as pruning objectives.•NSGA-II builds better non-dominated solution sets than local search heuristic.

论文关键词：Virtual tree pruning,Multi-objective optimization,Growth simulation,Simulated annealing,NSGA-II

论文评审过程：Received 13 January 2020, Revised 9 June 2020, Accepted 23 July 2020, Available online 28 July 2020, Version of Record 30 July 2020.

论文官网地址：https://doi.org/10.1016/j.eswa.2020.113792