Integrated Scheduling of Reheating Furnace and Hot Rolling Based on Improved Multiobjective Differential Evolution

Abstract

In the hot rolling mill, a cold slab is reheated in reheating furnace and then rolled into thin coils through hot rolling process. Traditional research on hot rolling mill generally takes the two processes as two separate single-objective scheduling problems, though they are closely connected and their optimization objectives are conflicting with each other. In this paper, the integrated scheduling of the reheating furnace and hot rolling is investigated in the view of multiobjective optimization. A mixed-integer programming model with two objectives is formulated for this problem, and a multiobjective differential evolution (MODE) algorithm is developed to solve this model. To make it easy for algorithm design, a hot rolling schedule (i.e., a sequence of slabs) is used to represent a solution and for a given solution, a heuristic with consideration of energy consumption minimization is presented to obtain the schedule of reheating furnace. To achieve the balance of exploration and exploitation, a novel mutation operator with adaptive leader selection, a crossover operator with feasibility consideration, and a guided multiobjective local search are designed. Computational results based on simulated data illustrate that the integrated scheduling is superior to the traditional two-phase scheduling method used in practice and literature. Further results illustrate that the proposed MODE algorithm is effective and superior to some other multiobjective evolutionary algorithms.

Research on Continuous Casting–Hot Rolling Scheduling Model Involving Reheating Furnace Conversion Mode and Improved Bat Optimization Solution Algorithm

“…They solved the scheduling problem in the reheating furnace well by specifying a scheduling scheme with the objective of minimizing the total penalties, but their research did not integrate well with the scheduling of the hotrolling mill. Li and Tian [22] established an integrated scheduling model for reheating furnaces and hot-rolling mills and adopted a multi-objective differential evolution algorithm for different optimization objectives of reheating furnaces and hot-rolling mills. They considered reducing unnecessary heating time in the reheating furnace and minimizing total changeovers in the hot-rolling mill to achieve optimal scheduling.…”

Multi-Mode Model Predictive Control Approach for Steel Billets Reheating Furnaces

“…Level 3 systems refer to production scheduling and to the computation of the temperature profile of each piece to be reheated/rolled. Systems located at level 3 are reported in [20][21][22][23][24][25]. A review of planning and scheduling methods for hot rolling mills in steel production is reported in [20].…”

“…It is thus capable of guaranteeing the most energy-efficient reheating operations by preserving logistics performances. In [23], the integrated scheduling of the reheating furnace and hot rolling is investigated in view of multi-objective optimization. A mixed-integer programming model with two objectives is formulated for this problem, and a multiobjective differential evolution algorithm is developed to solve this model.…”

System of Energy-Saving Optimal Control of Metal Heating Process in Heat Treatment Furnaces of Rolling Mills

“…The industry-average fuel consumption of the conventional metal heating process is 1.6 GJ/t [1], or 18% of the total specific energy costs of rolling steel. The figure could be lowered by altering the rolling technology, improving the furnace design, and optimizing the production planning [2][3][4] or the heat-treatment furnace parameters [5].…”

“…The authors of [4,[13][14][15][16][17] considered various approaches to dynamic optimization that can generate the blank heating trajectories to the specified criteria. Possible optimization criteria include fuel efficiency and heating quality.…”