Research On Steel-Pipe Job Scheduling Based On Genetic Algorithm

With the rapid development of global economic integration and increasinglydiversified market needs, customer orders are required to develop into multi varietiesand small batches. This kind of order mode will dominate the steel pipemanufacturing enterprises. Under this mode, the improvement of productionefficiency for the steel pipe manufacturing enterprises relies heavily on how toarrange the production plan and how to carry out the production scheduling.The seamless steel pipe production is a complicated process, which includes thetube billet continuous casting, hot rolling, colddrawing, pickling lubrication, coldrolling, annealing, straightening, immersion oil, surface treatment and so on. Theorders may use the same machine in different stages of the process, namely thereentrancy in manufacturing process, which will increase the competition of the rightsto use machinery equipments, prolong the wait-time for the orders and thus make thesteel pipe production scheduling more complex. Therefore, the production schedulingof these processes is not only the core issue for the steel pipe manufacturingenterprises but also the difficult problem for workshop scheduling issues.On the basis of a detailed introduction of the purpose, background andsignificance of the current study, the thesis firstly discusses the importance of thestudy for steel pipe production and analyzes the development of workshop productionscheduling and steel pipe production scheduling at home and abroad. Secondly, thethesis studies the characteristics and classifications of workshop scheduling issues andexplores into scheduling strategies for steel pipe production.Thirdly, the thesisreviews back the main course and study methods of steel pipe production schedulingissues and introduces the basic principle, handling process, basic operational steps andfeatures of genetic algorithm. Based on the application of genetic algorithm in thepractical problems, steel pipe production scheduling is analyzed in detail and modeled mathematically in the minimum completion time.And then the current study carriesout a simulation experiment and describes the software implementation of simulationsystem. Through data analysis in the simulation process, the current study overcomesthe defects of the general studies’ formal mathematical description of steel pipeproduction scheduling which is based on genetic algorithm. At last, the study gets aresult for optimal scheduling by means of simulation experiment. And the result hascertain guiding significance for production and proves the feasibility and effectivenessof genetic algorithm on the steel pipe work shop scheduling issues.