**Zhengbiao Hu, Dongfeng He \*, Wei Song and Kai Feng**

Department of Ferrous Metallurgy, School of Metallurgical and Ecological Engineering, University of Science and Technology Beijing, Beijing 100083, China; liupingze2019@163.com (Z.H.); songweiustb@163.com (W.S.); WeiRunWeiUSTB@126.com (K.F.)

**\*** Correspondence: hedongfeng@ustb.edu.cn

Received: 25 October 2019; Accepted: 18 December 2019; Published: 1 January 2020

**Abstract:** Batch-type hot rolling planning highly affects electricity costs in a steel plant, but previous research models seldom considered time-of-use (TOU) electricity pricing. Based on an analysis of the hot-rolling process and TOU electricity pricing, a batch-processing plan optimization model for hot rolling was established, using an objective function with the goal of minimizing the total penalty incurred by the differences in width, thickness, and hardness among adjacent slabs, as well as the electricity cost of the rolling process. A method was provided to solve the model through improved genetic algorithm. An analysis of the batch processing of the hot rolling of 240 slabs of different sizes at a steel plant proved the effectiveness of the proposed model. Compared to the man–machine interaction model and the model in which TOU electricity pricing was not considered, the batch-processing model that included TOU electricity pricing produced significantly better results with respect to both product quality and power consumption.

**Keywords:** hot rolling; TOU electricity pricing; hot rolling planning; genetic algorithm
