Study On Modeling And Optimization Algorithms For Rolling Line Capacity Planning Problem In Iron And Steel Industry

In recent years, with the changing market environment and the sharp market competition, the production requirements are becoming small-lot, multi-item and shortened-delivery-cycles. The characteristics of small-lot multi-item productions make the production path becomes more complex and changeable, and the characteristics of shortened delivery lead to the bottlenecks of production. Both of them are restricting the capacity of the iron and steel enterprises. Therefore, study on the capacity planning problem in iron and steel industry has great realistic significance.The capacity planning problem refers to that planners reasonably select a set of customer orders, which needs to meet the material balance, capacity constraint balance and on-time delivery, from the existing contracts resource pool in order to achieve maximum economic benefit under present multiple constraints. The capacity planning problem essentially belongs to optimization problem. The previous literature mostly pays attention to scheduling problems. However, according to the site actual demand, this paper focuses on contracts selection and production problem, which is more upstream during the contracts planning process.With the characteristics of capacity planning problem, a optimization model is formulated. The objective is to maximize weighted-sum contracts. The main constraints including production capacity of equipment, delivery, material balance and non-process path are all taken into consideration in the model.According to the model’s characteristics, an algorithm based on PBIL and linear programming is proposed to solve this problem in this paper. Firstly, this algorithm is to design PBIL with0-1chromosome encoding, and each chromosome represents a selection scheme of orders. And then, the linear programming model is used to calculate the fitness value for each chromosome. In the end, after several iterations the optimal order-selection scheme could be obtained. Experiments on practical production data indicate that the proposed model and algorithm can find a near optimal solution within reasonable time, which reflects the reasonableness of the model and the effectiveness of the algorithm.Based on the model and the algorithm, capacity planning system is developed. The design of system,database, and interface is carried out. And then, we use some programming languages to develop and debug this system. This system can effectively reduce the idle rate of the equipment, improve the utilization rate of the equipment, avoid the shortcomings of planners production scheduling, including more time and effort and poor precision, and provide enough decision support for planners.