Model and algorithm for scheduling reheating furnace
加热炉优化调度模型及算法研究

Reheating furnace is the major equipment in the hot-rolled production. Improving the scheduling of reheating furnace is an effective way to reduce the energy consumption and production costs. According to the production process and constraints on the reheating furnace, we propose a mathematical model for scheduling the reheating furnace, and present a scatter search(SS) algorithm to solve this model. We also design the random-variable-sequence-based voting combination operator(RVSBVCO) and the one-point-crossover combination operator(OPCCO). From the production data of an ironand-steel production enterprise, we randomly generate 40 instances for testing the model and the algorithm. The impact on the effectiveness and efficiency of the algorithm from the sizes of reference sets and two combination operators is evaluated and compared with the results obtained from the genetic local search(GLS) algorithm. Results show that the proposed model and algorithm are effective for solving the reheating furnace scheduling problem.