Decision-making Optimization System For Logistics Equipment Scheduling In Iron And Steel Industry

Along with increasing demand for iron and steel, the logistics scheduling problem in steel production becomes a hot issue for domestic and foreign research. Because of the high cost and limited quantity of the facilities in the iron and steel industry, the logistics equipment scheduling problem becomes a bottleneck problem in logistics scheduling domain gradually. In this paper, based on the background of the logistics equipment scheduling problem, which generally exists in ore material, product and half-finished product of iron and steel enterprise, we study the logistics equipment scheduling problem of ore material yard and the logistics equipment scheduling problem of batch annealing process.(1) The logistics equipment scheduling problem of ore material yardThis question is a reclaimer scheduling problem. It is to decide the rout of reclaimers and the start time of each taking materials operation, accroding to the characteristics of ore material yard and the plan of taking materials. The main constraints are the time window constraint and the demand constraint of materials. In view of the material supply system and the restraints of reclaimer working process in ore material yard, a multi-target mixed mathematics programming model is built for this problem.The objective is to the minimize operation cost of ore material yard, maximize the utilization and the equilibrium ratio of reclaimers.In ore material yard, a kind of ore material must be deposited in different ore material strips and one ore material stack can be just reclaimed by only one reclaimer. According to the characteristics of ore material yard, the problem is divided into two phases, one is the selection problem of ore material stacks, another one is reclaimer scheduling problem. In the first stage, a know-how heuristics is selected to get an initial solution, and then the scatter search algorithm is used to optimize the solution. A natural number classification encoding method and FIFO decoding way is proposed in the process. We also adopt three kinds of reference sets, three kinds of subsets as well as three kinds of combined strategies to guarantee the quality and the dispersivity of the solutions. Because of the time restraint, the feasibility of the solution is very difficult to be guaranteed in the process. Therefore, we use the penalty strategy to increase search coverage. The result obtained in the first stage is the input of the second stage. In order to raise the utilization and the equilibrium ratio of the reclaimers, a1-1exchange method is proposed, which is to exchange the different type of ore material as well as the different material stacks of the homogeneous ore materials. To prove the effectiveness of the algorithm, the random data based on actual production has been tested. From the computational result, we can find that the proposed algorithm can effectively solve the logistics equipment scheduling problem of ore material yard, save more operation cost of ore material yard and improve the utilization and equilibrium ratio of reclaimer.By combining the study of logistics equipment scheduling problem and actual situation, the logistics scheduling optimization software of ore material yard is designed. The function of the software includes data maintenance, stock management, ore material plan and equipment scheduling.(2) The logistics equipment scheduling problem of batch annealing processIn view of the complex batch annealing process as well as the limited resources, we schedule the whole batch annealing procedure to increase the production efficiency. The objective is to minimize the maximum completion time. First, because the heating and cooling procedures take up most of the processing time, a combination algorithm combines the heuristics based on Johnson’s rule with the scatter search algorithm is proposed to solve this problem. In the scatter searching algorithm, a natural number without redundancy encoding method is adopted to guarantee the feasibility of the solution. Owing to the complexity of the problem, it’s hard to decode directly, so a two-phase encoding method is designed to simplify the decoding process. In the combination method, a one-point-overlapping strategy and a two-plan-exchange strategy are adopted to guarantee the feasibility of the solution. Finally, the random data based on actual production has been tested. From the computational result, we can find that the algorithm proposed in this paper can effectively solve the logistics equipment scheduling problem of batch annealing process, reduce the maximum completion time, and raise the production efficiency.