A prediction-based online soft scheduling algorithm for the real-world steelmaking-continuous casting production

作者：

Highlights：

• An uncertain SCC scheduling problem arising from steelmaking industry is studied.

• A soft schedule that consists of critical decisions and characteristic indexes is introduced.

• A prediction-based online soft scheduling algorithm is proposed to solve this problem.

• A surrogate model predicts characteristic indexes with trade-off between cost and penalty.

• An e event-triggered dynamic optimization algorithm is proposed to obtain entire soft schedule.

• A heuristic method is proposed for dispatching jobs in real time.

摘要

•An uncertain SCC scheduling problem arising from steelmaking industry is studied.•A soft schedule that consists of critical decisions and characteristic indexes is introduced.•A prediction-based online soft scheduling algorithm is proposed to solve this problem.•A surrogate model predicts characteristic indexes with trade-off between cost and penalty.•An e event-triggered dynamic optimization algorithm is proposed to obtain entire soft schedule.•A heuristic method is proposed for dispatching jobs in real time.

论文关键词：Scheduling,Uncertainty modelling,GPR,Steelmaking

论文评审过程：Received 7 January 2016, Revised 4 August 2016, Accepted 7 August 2016, Available online 10 August 2016, Version of Record 23 September 2016.

论文官网地址：https://doi.org/10.1016/j.knosys.2016.08.010