Articles

National grain reserve is important in terms of responding to disasters and the unbalance between supply and demand in many countries. In China, the government supplements grain supply through online auctions. This study focuses on the auction policy of national grain reserve. We develop an agent-based simulation model of China’s wheat market with detail descriptions of different agents, including national grain reserve, grain trading enterprises and grain processing enterprises. Based on this model, the Optimal Computing Budget Allocation (OCBA) simulation optimization method is adopted to analyze the characteristics of optimal decision variables under different scenarios, with an objective to minimize the fluctuation of wheat price. We obtain some insights about operations of national grain reserve. As the first agent-based simulation model about national grain reserve and grain market, this model can be widely used in agricultural economics, and can provide policy supports to the government.

Simulation is a widely used technique for analyzing and managing supply chains. Simulation software packages offer standard libraries for selected functions and application areas. However, no commercial or freeware simulation tool proposes building blocks specific to semiconductor manufacturing.

A hierarchical production planning structure enables manufacturing systems to handle customer disturbances with different measures on different planning levels. Two different kinds of customer order behavior can be observed and are as well discussed in literature.

The paperwork presented by Victor Romanov, Dmitry Yakovlev and Anna Lelchuk describes modification of wealth distribution among the customers. A simulation model created by them helps to analyze the following interrelated spheres, such as labour market, stock market, enterprise investment strategy, tax level.

Agent-based modeling and simulation (ABMS) is a new approach to modeling systems comprised of autonomous, interacting agents. Computational advances have made possible a growing number of agent-based models across a variety of application domains. Applications range from modeling agent behavior in the stock market, supply chains, and consumer markets, to predicting the spread of epidemics, mitigating the threat of bio-warfare, and understanding the factors that may be responsible for the fall of ancient civilizations.

This article discusses General Motors’ North American Enterprise Model, a system dynamics model of the entire North American automobile market. The Enterprise Model takes a broad look across the corporation and its marketplace, combining internal activities such as engineering, manufacturing and marketing with external factors such as competition for consumer purchases in the new and used vehicle marketplaces. Eight groups of manufacturers compete monthly for a decade across eighteen vehicle segments, making segment-by-segment decisions about price, volume and investment.

The presentation shows you how to develop simulation models, choose abstraction level and methodology.

This paper presents a hybrid simulation model for the management of an eye condition called age-related macular degeneration, which particularly affects the elderly. The model represents not only the detailed clinical progression of disease in an individual, but also the organization of the hospital clinic in which patients with this condition are treated and the wider environment in which these patients live (and their social care needs, if any, are met). The model permits a ‘whole system’ societal view which captures the interactions between the health and social care systems