Application Of Multiagent Simulation Modeling To Forecast Milk Receiving Process

This research paper discusses the application of multiagent simulation model of production processes by reference to milk receiving and storage. The paper describes basic parameters for general models, and presents the experiment results obtained during the model processing, as well as the approach towards implementation of the multiagent system employing AnyLogic simulation environment. The introduction of general technique to plot multiagent simulation models allows to use digital tools to create a virtual copy of the true-life processes with the possibility to provide forecast and identification of the food production industries. The employment of simulation modeling enables refinement of the production process under study, identification of its weaknesses, and provision of the expert opinion on improvement of production processes and as regards the results of virtual testing thereof.

Factors Affecting the Evolution of Advanced Manufacturing Innovation Networks Based on Cloud Computing and Multiagent Simulation

Facing the pressure of low-cost competition brought by the homogenization of commodities, the manufacturing industry seeks to survive by providing services. By providing outsourcing of value-added services to date, we are focusing on innovation in our business model. With the advancement of science and technology, manufacturing innovation is facing higher challenges, especially the popularization of the Internet, which makes the manufacturing industry have to move closer to new industries. Based on cloud computing, this paper conducts a multiagent simulation on the evolution factors of the innovation network of advanced manufacturing. This article takes three types of simulation subjects: evolutionary network, manufacturing (cluster), and innovation evolution system as the research objects. The factors affecting the evolution of the research are innovation resources, innovation opportunities, innovation desire, innovation pressure, relationship strength, network scale, and network scope. Network differences carry over variable indicators and analyze quantitative regression indicators and then build a research model. The research results show that the average conversion efficiency of the manufacturing industry (0.523) is significantly lower than the average R&D innovation efficiency (0.725), which to a certain extent indicates that the manufacturing industry still has weak links in the export conversion stage at the back end of the innovation value chain. Some of the companies may have problems such as low ability to transform scientific and technological achievements and insufficient export competitiveness of high-tech products, which to a large extent affects and restricts the improvement of manufacturing export transformation efficiency.

Multiagent Simulation of Demand Flexibility Integration in Local Energy Markets

Overcoming the issues associated with the variability of renewable generation has become a constant challenge in power and energy systems. The use of load flexibility is one of the most promising ways to face it. Suitable ways to incorporate flexibility in the electricity market, in addition to the already challenging integration of distributed generation primary sources, are therefore crucial. The integration of prosumers and consumers flexibility in the market is, however, not straightforward, as current wholesale and retail market structures are not prepared to deal with the current and future needs of the system. Several models for local energy markets have been studied and experimented; but there it is still not clear what is the most efficient way to integrate the dynamic participation of demand flexibility in this type of local markets.

Research on the Complexity Mechanism of Decoy Strategies Based on Multiagent Simulation

Competition and diffusion of products are of great significance to companies. In this study, various true decoy strategies are constructed using different combinations of price and quality. This paper then analyzes the performance of strategies using different product competition and diffusion scenarios. The influences of neighbor nodes, reconnection probability, and herd mentality on decoy effects are explored. The results show that setting an appropriate true decoy can enhance the competitiveness of a target product to some extent. Conversely, an inappropriate decoy strategy will play a negative role, encroaching on market share. In terms of effects, changes in neighbor nodes, reconnection probability, and herd mentality will not influence the direction of the evolution of a product for the same true decoy strategies. However, the speed of evolution will be affected. These findings provide a theoretical basis for enterprises taking action to enhance product competitiveness in the market.