Intelligent Simulation On Division And Cooperation Behaviors Of Enterprise

Under the circumstance of increasing competitive market, the internal and external environment is increasingly complex for enterprises, and the diversification of demand and uncertainty are a challenge to various types of enterprises. For quick response to personalized demand of customers, production companies must optimize the traditional operation mode to increase production flexibility and agility, and also the companies should collaborate to build the virtual enterprise to respond to market opportunities; in addition, virtual software enterprises, a particular form of virtual enterprise, also attracted scholars increasingly. In this paper, form the view of enterprise collaboration, it is selected the typical forms of enterprises, such as manufacturing enterprise, virtual enterprise and virtual software enterprise, and based on this enterprises, the related multi-agent simulation models are established, and according to the simulation results, the management recommendations on dynamic behaviors were proposed. The main study works of this paper are the following.Firstly, this paper analyzed the limitations of kanban control strategy on pull production systems, discussed the similarity between kanban control strategy and the fixed threshold model of ant colony labor division. In order to compensate for the lack of global optimization and achieve production balance, we proposed a new kanban control strategy. We improved the fixed threshold model of ant colony labor division, re-designed of the environment, property characteristics of state transition rules of ants, and established a multi-state model of ant colony division of labor. Through an implementation process example of the multi-state model of ant colony division of labor, the algorithm steps were given. Then, we select a typical example of the production process, used the model to simulated. The results showed that the dynamic kanban control strategy based on multi-state model of ant colony division of labor can balance the production efficiency of processes, increase the ability of production systems to respond to changeable production tasks, reduce restrictions on the key processes to achieve global optimization, increase the smoothness of production process, balance the workload.Secondly, this paper took the self-management teams of virtual enterprise as a example, analyzed the double-layer learning behaviors of self-management teams defined the team members and tasks as different agent. Based on the self-ability estimation error rate and mutual capacity estimation error rate, we established a multi-agent simulation model and achieved STLBMSS by Visual Basic, confirmed the model by an instance. The results revealed influence mechanism of the double double-layer learning behaviors on team task treatment efficiency, and also showed the effectiveness of STLBMS for analyzing the learning behavior of self- management team.Thirdly, based on the complex adaptive system (CAS) theory, this paper analyzed overall operation and emergence phenomenon of the virtual software enterprises from formation to dissolution, used the multi-agent modeling and simulation method, abstracted the virtual software enterprises as agents, established a virtual software enterprise evolution multi-agent model and used Anylogic to achieved the model. According to simulation results, we found the mechanism of dominant selecting partners and the development trends of enterprises on the evolution process of virtual software enterprises. The success of virtual software enterprises largely depend on the process of its formation. The most crucial aspect of formation is choosing the right partners. In this paper, we took the partner selection of virtual software enterprises as study object, analyzed micro-mechanism of the partner selection, and used multi-agent modeling and simulation method to establish a multi-agent model, designed simulation experiments to study partner selection mechanism under different goals. The results showed that lowest cost method, shortest duration method and best quality method achieved the optimal goal, but less stable. The comprehensive best method achieved the balance between the total duration and total quality.