Academic articles

Auction policy analysis: an agent-based simulation optimization model of grain market


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.

Increasing capacity utilization of shuttle trains in intermodal transport by investing in transshipment technologies for non-cranable semi-trailers


For shuttle trains with a fixed transport capacity which are the dominant operating form in intermodal transport, increasing capacity utilization is of crucial importance due to the low marginal costs of transporting an additional loading unit. Hence, offering rail-based transport services for non-cranable semi-trailers can result in additional earnings for railway companies. However, these earnings have to compensate for the investment costs of the technology. Based on a dynamic investment calculation, this paper presents a simulation model to evaluate the economic profitability of transshipment technologies for non-cranable semi-trailers from the railway company’s perspective. The results depend on the capacity utilization risk faced by the railway company. In particular, if the railway company does not sell all the train capacity to freight forwarders or intermodal operators on a long-term basis, investing in technology for the transshipment of non-cranable semi-trailers can be economically profitable.

A structured approach for constructing high fidelity ED simulation


This paper presents a structured approach to building a high-fidelity simulation for an emergency department. Our approach has three key features. First, we use the concept of modules as a building block for modeling. A module is a minimum unit that has clinical or administrative meanings in ED operation, and it consists of low level operational activities. Second, we use a structured template to formally represent modules, and we adopt notations and grammars from the business process modeling notation. This provides an enhanced clarity and transparency, which proves very useful in extracting necessary data from a hospital database or from interviewing ED staff. Finally, we define an interface, specifically data structure and handler, for converting information represented in the modules into simulation languages. This interface makes it possible to seamlessly link the modeling process to the implementation process in the simulation construction.

An agent-based framework to study occupant multi-comfort level in office buildings


With the trend towards energy efficient buildings that diminish fossil fuel usage and carbon emissions, achieving high energy performance became a necessity. Allowing occupants to be actively involved during the design and operation phases of buildings is vital in fulfilling this goal without jeopardizing occupant satisfaction. Although different occupant behavior types were considered in prior research efforts, recent tools did not however examine simultaneously visual, thermal and acoustic comfort levels. This paper presents work targeted at efficiently studying occupant multi-comfort level using agent-based modeling with the ultimate aim of reducing energy consumption within academic buildings. The proposed model was capable of testing different parameters and variables affecting occupant behavior. Several scenarios were examined and statistical results demonstrated that the presence of different occupant behavior types is deemed necessary for a more realistic overall model, and the absence of windows results in an acoustic satisfaction with a decrease in (HVAC) use.

Improving patient access to a public hospital complex using agent simulation


This paper uses agent based simulation to assess the effect of redesigning the points of access to a major public hospital complex in Chile, where nearly 15,000 people will pass through daily. The study is carried out by simulating pedestrian traffic in order to calculate density maps and service levels in hospital access and ramps. The simulation allows us to evaluate the flow of people and assess the layout performance, by identifying high patient flow areas and congested pedestrian traffic zones. By using this approach, it is possible to suggest changes to the original design and to improve pedestrian flow at hospital access points and ramps. The suggested changes reveal that pedestrian indicators could be improved, which in turn would improve the level of satisfaction of patients, relatives, and hospital personnel. A higher satisfaction level would help to reduce stress linked to hospital facilities and crowded spaces.

From desktop to large-scale Model Exploration with Swift/T


As high-performance computing resources have become increasingly available, new modes of computational processing and experimentation have become possible. This tutorial presents the Extreme-scale Model Exploration with Swift/T (EMEWS) framework for combining existing capabilities for model exploration approaches (e.g., model calibration, metaheuristics, data assimilation) and simulations (or any “black box” application code) with the Swift/T parallel scripting language to run scientific workflows on a variety of computing resources, from desktop to academic clusters to Top 500 level supercomputers. We will present a number of use-cases, starting with a simple agent-based model parameter sweep, and ending with a complex adaptive parameter space exploration workflow coordinating ensembles of distributed simulations. The use-cases are published on a public repository for interested parties to download and run on their own.

Agent-Based Modeling: an Introduction and Primer


Agents are self-contained objects within a software model that are capable of autonomously interacting with the environment and with other agents. Basing a model around agents (building an agent-based model, or ABM) allows the user to build complex models from the bottom up by specifying agent behaviors and the environment within which they operate. This is often a more natural perspective than the system-level perspective required of other modeling paradigms, and it allows greater flexibility to use agents in novel applications. This flexibility makes them ideal as virtual laboratories and testbeds, particularly in the social sciences where direct experimentation may be infeasible or unethical. ABMs have been applied successfully in a broad variety of areas, including heuristic search methods, social science models, combat modeling, and supply chains. This tutorial provides an introduction to tools and resources for prospective modelers, and illustrates ABM flexibility with a basic war-gaming example.

Harnessing advances in computer simulation to inform policy and planning to reduce alcohol-related harms


Alcohol misuse is a complex systemic problem. The aim of this study was to explore the feasibility of using a transparent and participatory agent-based modelling approach to develop a robust decision support tool to test alcohol policy scenarios before they are implemented in the real world. Methods A consortium of Australia’s leading alcohol experts was engaged to collaboratively develop an agent-based model of alcohol consumption behavior and related harms. As a case study, four policy scenarios were examined.

Argus Invasive Species Spread Model Constructed Using Agent-based Modeling Approach and Cellular Automata


The stochastic Argus Invasive Species Spread Model (AISSM) is constructed using an Agent-Based Modeling (ABM) approach with cellular automata (CA) to account for spatial relationships and changes in those relationships over time. The model was constructed to support a wide range of geographical locations; however, this paper focuses on its application in the state of California. A timeseries of daily historical weather observations on a 6- kilometer grid was obtained for six weather variables important to insect and disease development. Weather conditions were then simulated using the K- nearest neighbor (K-nn) regional weather generator. The weather simulations were summarized into a monthly time-step and coupled with satellite land cover imagery to identify a habitat quality for each simulated month. This information was combined with the introduction of invasive species in the AnyLogic™ modeling environment. The spread of invasive species is driven by the habitat quality layer, which regulates its dispersal rate.

A multimethod computational simulation approach for investigating mitochondrial dynamics and dysfunction in degenerative aging


Research in biogerontology has largely focused on the complex relationship between mitochondrial dysfunction and biological aging. In particular, the mitochondrial free radical theory of aging (MFRTA) has been well accepted. However, this theory has been challenged by recent studies showing minimal increases in reactive oxygen species (ROS) as not entirely deleterious in nature, and even beneficial under the appropriate cellular circumstances. To assess these significant and nonintuitive observations in the context of a functional system, we have taken an in silico approach to expand the focus of the MFRTA by including other key mitochondrial stress response pathways, as they have been observed in the nematode Caenorhabditis elegans. These include the mitochondrial unfolded protein response (UPRmt), mitochondrial biogenesis and autophagy dynamics, the relevant DAF-16 and SKN-1 axes, and NAD+-dependent deacetylase activities. To integrate these pathways, we have developed a multilevel hybrid-modeling paradigm, containing agent-based elements among stochastic system-dynamics environments of logically derived ordinary differential equations, to simulate aging mitochondrial phenotypes within a population of energetically demanding cells.