| Since from the industrial revolution,world gradually became an industrial society. Industrial capacity has become the most important indicator of the comprehensive national strength. So many states invested enormous resources in research to let themselves strong. Especially after World War II, various industrial power countries successively involved in the use of information technology in manufacturing, and then generate international, global manufacturing pattern. Our country is to become the world’s factory. In order to maintain our country’s share of world manufacturing field, more in-depth study of Industrial production becomes imperative. That is essential should be management workshop. Especially shop scheduling problem is the most crucial breakthrough. Job Shop Scheduling is the actual production problems after extracting the key factors, simplified into a model, that under the premise of certain resources and production constraints, reasonable allocation of production equipment, reasonable arrangements for production order, completion of the production plan in the shortest time.With basis of work experience in FOXCONN, the world’s largest manufacturer, in the consumer electronics production sector. Combined with improve genetic algorithm, research on shop scheduling problem. Propose new genetic (algorithm-auxiliary populations) which has contains assist mixed multi-group. From the engineering point of view, pointed out the shortcomings of standard genetic algorithm and adaptive genetic algorithm on the Job Shop Scheduling Problem. New genetic algorithm has better use value in the consumer electronics workshop production scheduling, effective solution to the drawbacks of genetic algorithms, such as poor local search capability, solving with long time, low search efficiency in the later stage of evolution.Finally realized that using a variety of genetic algorithms to solve job shop scheduling problem.Evaluate the combination of work experience in Consumer Electronics Division (CCPBG) CNB-molding department, produce SONY notebook. The actual calculation of the efficiency of the algorithm was tested, applied to shop scheduling simulation system, the results show that multi-population genetic algorithm is feasible, solving faster, higher efficiency of global convergence, with good usability, efficiency on the shop scheduling problem, significantly improve the productivity of two production line. |
