Variable Neighborhood Search based Multi-objective Optimization Method for Batch Scheduling of Hot-rolled Bar

• 1、Dongling School of Economics and Management, University of Science and Technology Beijing, Beijing 100083
• 2、 Engineering Research Center of MES Technology for Iron and Steel Production, Ministry of Education of China, Beijing 100083

Abstract：According to the influence of process conditions and due date on the continuous production of rolling units, a batch scheduling problem of hot-rolled bar was studied. A mathematical model with three objectives to minimize setup times, tardiness penalties and steel grade bounce penalties was proposed, and a method of variable neighborhood search algorithm embedding the earliest due date first rule was proposed to solve the model. With the consideration of the constraints in the model, an initial solution was generated by constraint satisfaction technology. Then, to meet the actual production needs, a variable neighborhood search method was designed to minimize setup times, which is considered as a primary objective. In this algorithm, a hybrid operator is applied in shaking and local search, and the idea of simulated annealing is introduced to take control of the acceptance of new solutions. Meanwhile, in order to minimize tardiness penalties and steel grade bounce penalties, Earliest Due Date first rule and steel grade sorting rule are applied. Experiment results show that the model and algorithm are feasible and effective.

Keywords： batch scheduling hot-rolled bar variable neighborhood search multi-objective optimization constraint satisfaction