Enterprise Group Order Allocation Model

Based on the allocation and management of enterprise groups, group used of the unfired management, which was good for the overall allocation optimization. It made the Group to get the maximum benefit, and enhance the Group's competitiveness in the industry. The order was directly distributed by the Group leaders in the old time, and the decision the leaders made was based on past experience. In other words, it had little theoretical basis. The main word of this paper is to propose the theoretical basis for the order. On this basis, enterprise group can achieve maximum production and profit maximization, which wants to provide basis of the order distribution of the enterprise groups and improve the management capacity of enterprises.This article is divided into four parts:The first part shows the purpose, significance and research methods. It plays an important role for the survival of the enterprise group, because it is the increasingly fierce competitive environment nowadays, so the orders must be reasonable distribution. It just does like that, the Group could play a greater role in resource, which get maximum production and profit maximization.The second part shows that multi-objective optimization problem, and its basic concept and application of the basic steps, etc. The goal of the multi-objective problem is to find the optimal equilibrium between more than one objective function. The second model in this article is to use multi-objective genetic algorithm to solve, so we introduce the multi-objective genetic algorithm to let readers can better understand it.The third part shows the current problem of the order management of the Enterprise Group, so we established a multi-objective model for order allocation for this problem, and defines the corresponding parameters, and gets the model solution. At last, we illustrate its availability by an application example.Finally, based on the above single model, we propose the multi-objective order allocation model, more details about the order allocation process. By the way, the data we use is the application of the model data mentioned above. The model is solved through genetic algorithm. The results showed that the multi-objective model make the Group has a certain increase profits.