| Locomotive overhaul is the foundation of locomotive depot organizing transportation and production activities, and a powerful guarantee for the normal operation of locomotive. It has played an important role in improving locomotive operation efficiency. Thus increasing overhaul quality and management level and enhancing process control have been crucial in ensuring safety and improving efficiency. Consequently, to establish and perfect modern locomotive overhaul system is a significant task.Locomotive overhaul system is an information system that offers support for leadership decision-making. It is to meet the needs of overhaul standardization, routinization and informatization. Overhaul management and production process as the main lines, the system is aim to control locomotive overhaul quality.Work order management has played a very important role in the whole overhaul process control. The rationality of order scheduling is directly related to the efficiency and quality of locomotive overhaul. Therefore, effective and reasonable work order scheduling is the key to ensuring overhaul high efficiency and high quality.The topic of this paper comes from the work order scheduling implementation method in the project "LanXi locomotive depot overhaul system". It is mainly aimed at the allocation of human resources, taking into account human resource capacity and diversity of skills. The order scheduling mathematical model has been established and solved by virus evolutionary genetic algorithm. It has been proved scientifically,and verified the superiority of virus evolutionary genetic algorithm for solving this problem. Finally, intelligent scheduling of the work order has been achieved in the "LanXi locomotive overhual system" and everyone can do his best.The main contents of this paper were as followed:(1) This paper studied the whole locomotive overhaul system, and the deficiency of work order scheduling was analyzed in current overhaul system, It main includes two points:First, maintenance workers using paper orders On-site, commuting between preparation workshop and office lead to low work efficiency and high work intensity. Second, artificial distribution of work order scheduling with more empirically, very few consider the skills of workers and diversity of ability differences and lack of scientific.(2) We do a deep research on the virus evolutionary genetic algorithm, and then a few numerical examples validated the performance of the algorithm. The results show that, compared with genetic algorithm, virus evolutionary genetic algorithm can obtain optimal solutions with shorter computing time and less generations. (3) The work order scheduling mathematical model was established about allocation of human resource. The virus evolutionary genetic algorithm is used in the model and is verified by an example in this thesis Experimental results show that the virus evolutionary genetic algorithm could get a better solution at a rapid pace. That is in the premise of give full consideration to the operator different skills, can get a meet quality and schedule requirements of the optimum solution.(4) The mobile electronic work order scheduling system was designed. The system has realized intelligent distribution of the work order scheduling and solved manual input of data in traditional locomotive overhaul system, achieving the two-way implementation transmission of overhaul data, reducing the labor intensity,improving work efficiency and quality.(5) Using of computer simulated the practica work order scheduling, the results show: through computer for intelligent allocation of work order, the workers complete the task time in less than manually assigned, fully embodies the advantages of word order intelligent allocation and rationality. |
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