Multi-objective stochastic project scheduling with alternative execution methods: An improved quantum-behaved particle swarm optimization approach

作者：

Highlights：

• A stochastic multi-objective project scheduling problem with alternative execution methods.

• An improved multi-objective QPSO algorithm is applied with sample average approximation.

• A two-stage learning strategy and chaotic operators are designed.

• Algorithm Validation through instances generated by the designed instance generator.

摘要

•A stochastic multi-objective project scheduling problem with alternative execution methods.•An improved multi-objective QPSO algorithm is applied with sample average approximation.•A two-stage learning strategy and chaotic operators are designed.•Algorithm Validation through instances generated by the designed instance generator.

论文关键词：Quantum-behaved particle swarm optimization,Two-stage learning strategy,Chaotic operators,Multi-objective,Stochastic durations,Resource-constrained project scheduling

论文评审过程：Received 14 February 2021, Revised 17 November 2021, Accepted 27 March 2022, Available online 6 May 2022, Version of Record 13 May 2022.

论文官网地址：https://doi.org/10.1016/j.eswa.2022.117029