A filtering genetic programming framework for stochastic resource constrained multi-project scheduling problem under new project insertions

作者：

Highlights：

• A HH-FGP framework is proposed to solve the SRCMPSP-NPI.

• The evolutionary process is divided to achieve PR sampling and generation.

• A new evaluation mechanism is proposed for depth range and attributes filtering.

• The search operators are improved to avoid producing PRs with illegal depth.

摘要

•A HH-FGP framework is proposed to solve the SRCMPSP-NPI.•The evolutionary process is divided to achieve PR sampling and generation.•A new evaluation mechanism is proposed for depth range and attributes filtering.•The search operators are improved to avoid producing PRs with illegal depth.

论文关键词：Filtering evolution,Genetic programming,Priority rule,Stochastic resource constrained multi-project scheduling

论文评审过程：Received 3 September 2021, Revised 18 January 2022, Accepted 12 March 2022, Available online 21 March 2022, Version of Record 22 March 2022.

论文官网地址：https://doi.org/10.1016/j.eswa.2022.116911