| With the growth of car ownership,the demand for tires has been increasing day by day.More and more tire corporations begin to set up distributed factories to reduce the cost of tire production and transportation.These distributed factories make the production scheduling problem more complex.When the planners map out a scheme,they need to consider more so that they can find a satisfactory production scheduling scheme.It is not only time-consuming and labor-consuming,but also difficult to ensure the optimal scheduling scheme if the optimal scheduling scheme is found only by human experience.That is the significance of studying the tire production scheduling.Traditional optimization methods often fail to obtain satisfactory scheduling schemes,or to say the solution of the problem facing such a NP-hard problem.In addition,various constraints in the actual production process,such as product variety constraints,productive power constraints,packing ability constraints,work time constraints,product delivery date constraints,production flow constraints and preference factory constraints.These constraints further increase the complexity of production scheduling problems.Based on the actual production scheduling demand of a large tire corporation in China,this paper studies a tire production scheduling problem among distributed factories,which can distribute orders among these factories.By seeking the optimal production scheduling scheme,the overall production cost and transportation cost can be reduced so that the social competitiveness of the corporation can be improved.The main work of this paper can be summarized into some aspects: First of all,on the basis of sufficient investigation,the objective and constraint conditions are extracted,and the demand analysis is formulated into accurate mathematical description.Through a series of formula derivation,a distributed tire production scheduling model is established.Secondly,an efficient evolutionary algorithm for solving the model is designed and implemented,including encoding strategy,crossover and mutation operator,modified operator and local search;thirdly,the production scheduling software including database and interface is designed and implemented;finally,the effectiveness of the algorithm is verified by comparing with other three classical algorithms;at the same time,the completeness of the system is tested and demonstrated. |
