Research On Optimization Of Hot Rolling Scheduling Implementation And Crane Scheduling Problems

In the production process of iron and steel enterprise,the slab yard is used to provide raw materials for hot rolling process and to put slabs which need to be rolled on roller table for rolling.At present,the low utilization efficiency rate of logistics equipment in slab yard directly reduces the logistics operation efficiency which affects the production efficiency of hot rolling production line.There are two major reasons for the low rate.On the one hand,the overlooked slab locations in the slab yard when rolling planning lead to a large number of shuffling operations.On the other hand,the unreasonable scheduling of the logistics equipment and the unreasonable execute sequence of logistics commands causing long operation path and no-load distance.Therefore,optimization of hot rolling scheduling implementation problem and crane scheduling problem are studied to optimize the preliminary hot rolling plan and crane operation process when completing the production tasks through mathematical modeling and intelligent optimization algorithm.Moreover,a decision support system is developed which incorporates in the achievements in this thesis.This thesis mainly studies around the following three aspects:(1)The optimization problem of hot rolling scheduling implementation is studied to optimize the preliminary hot rolling production plan with considering the hot rolling production process and the slab stacks information to decide which slabs to replace the preliminary planned slabs with the goal of minimizing the amount of shuffling operations in the plan implementation process and production transition costs.A mixed integer programming model is established,while CPLEX is used to solve small-scale problems to verify the model.According to the problem characteristics,the improved differential evolution algorithm with adaptive crossover and mutation parameters based on normal distribution is designed to solve large-scale problem.Through actual application,the results show that the proposed improved differential evolution algorithm outperforms the software used currently by 35.667%in the result,which indicating that the proposed method can effectively reduce the shuffling operations.(2)The crane scheduling problem is studied to optimize the crane commands which have been issued under the consideration of the operation condition of crane as well as the crane transportation capability to decide execution sequence of the commands and which ones executed concurrently.The linear integer programming model is established with the goal of minimizing the execution time of completing crane commands.CPLEX is used to solve small-scale problems to verify the model.According to the problem characteristics,an improved differential evolution algorithm with adaptive crossover and mutation parameters based on normal distribution is designed to solve large-scale problem.Through actual application,the results show that the proposed improved differential evolution algorithm outperformed the software used currently by 44.63%in the result,which indicating that the proposed improved differential evolution algorithm can effectively reduce the execution time of completing crane commands.(3)Based on the two problems above,the hot rolling scheduling implementation optimization and crane scheduling optimization decision support system is developed,of which the core is the model and proposed algorithm.This system consists of two function modules which are the hot rolling scheduling implementation optimization module and crane scheduling optimization module.These modules have the functions of automatic optimization,manual adjustment,the results calibration and results evaluation,achieve the effect of raising the utilization ratio of logistics equipment in slab yard.