A non-homogeneous approach to simulating the spread
of disease in a pandemic outbreak
Theo Wibisono and Dionne Aleman
(University of Toronto) and Brian Schwartz (Emergency Management Unit, Ontario
Ministry of Health and Long Term Care)
Abstract:
In the event of a pandemic outbreak, emergency
management units must coordinate an effective mitigation strategy to stop the
disease spread using limited resources. In order to develop a successful
response, it is necessary to have an accurate model of how the disease will
spread. Previously presented models largely rely on homogeneous mixing models,
which treat every member of the population as having identical infection risk.
Intuitively, such an assumption is unrealistic. Certain demographic groups
(e.g., healthcare workers, children and the elderly), have higher infection
risks. Additionally, behavioral patterns such as use of public transportation
impact infection risks. Using contact networks to represent the level of
contact between population members and census data to approximate geographic
location and travel patterns, we simulate the progression of a droplet-spread
disease through the Greater Toronto Area. The results are periodically
displayed on area maps using GIS software for visualization and planning
purposes.
Modeling of Supply Chain with Variation of
Inventory Systems at Nodes
Fernando Rafael Gonzalez Solano, Diana
Isabel Davila Ramirez, Marlloly Liseth Sumoza Suarez, and Luis Eduardo Ramirez
Polo (Universidad del Norte)
Abstract:
The proposed model is an attempt to analyze the
advantages of uses of different systems of inventory in a supply chain
involving nodes with different intentions in each one. This model is based on
to network of eight nodes distributed between plants, centers of
consolidation, distributors and markets with the purpose of simulating the
real behavior of to chain of this type.
Verifying the Design of a Cellular Manufacturing
System
Benny Tjahjono and Rossella Stama (Cranfield University)
Abstract:
This paper reports a simulation study to evaluate the
design of a cellular layout for the production of low volume, high variety of
products. The study aims to better understand the production capacity and the
potential problems that may arise in the future when more products variety are
introduced at smaller quantities. The model was built using a commercial tool
but the simulation parameters are stored in a spreadsheet allowing much
simpler coding of the routing logic and the data input. The experiments were
carried out to reduce bottleneck and to investigate the effect of different
batch sizes, machine breakdown and scrap, to the performance of the cellular
layout.
SDL Distributed Simulator
Pau
Fonseca i Casas (Universitat Politècnica de Catalunya)
Abstract:
Formalisms becomes an important tools since allows the
complete understanding of the model and helps in its implementation. However
only few simulation tools allows an automatic construction of a simulation
model based in a formalization of the system. SDL is a modern object oriented
formalism that allows the definition of distributed systems. It has focused on
the modeling of reactive, state/event driven systems, and has been
standardized by the International Telecommunications Union (ITU) in the Z.100
Since it is a graphical formalism simplifies the understanding of the model.
In this paper we show an implementation of a simulation infrastructure that
follows SDL formalization language. This infrastructure allows a distributed
simulation of the models without any modification to the model definition.
Since this infrastructure follows the SDL language formalism it is useful not
only for a production use but to teach formalisms and distributed simulation
concepts.
An XML-Based Language for DEVS
Components
Nicolas Günter Meseth, Patrick Kirchhof, and Thomas
Witte (University of Osnabrück)
Abstract:
An XML-based language for simulation components (XLSC)
is presented in this paper. The language is designed in a way that the
resulting components comply with the DEVS formalism. The objective is to model
the static structure of a component as well as its behavior (dynamic
structure). For execution of XLSC, an interpreter is prototypically
implemented in Java. The use of XLSC enables components to be exchangeable and
to be used with any DEVS simulator regardless of its implementation language.
Thereby, the interpreter acts as an interface between the model and the
simulator as it can directly execute the component’s functions.
A Comparison of Sequential Design Methods for RF
Circuit Block Modeling
Karel Crombecq (University of Antwerp), Dirk
Gorissen (Ghent University), Luciano De Tommasi (University of Antwerp) and
Tom Dhaene (Ghent University)
Abstract:
When modeling complex systems, the locations of the
data points are essential to the success of the algorithm. Sequential design
methods are iterative algorithms that use data acquired from previous
iterations to guide future sample selection. They are often used to improve an
initial design such as a Latin hypercube or a simple grid, in order to focus
on highly dynamic parts of the design space. In this paper, a comparison is
made between different sequential design methods on a real-world electronics
problem. Error-based and density-based methods are compared against a novel
hybrid technique which incorporates both an error-based measure, using
gradient estimations of the objective function, and a density-based measure,
using a Voronoi tessellation approximation. The test results indicate that a
considerable improvement of the average model accuracy can be achieved by
using this new approach.
Panoramic Screen-Based Simulation with Dynamic
Background
Samsun Lampotang and David E. Lizdas (University of
Florida), John J. Tumino (Army National Guard) and Nikolaus Gravenstein and
Harshdeep S. Wilkhu (University of Florida)
Abstract:
A national focus group evaluating a preliminary
screen-based simulation found navigation between multiple screens representing
different operating room (OR) entities challenging. Consequently, we
re-designed the simulation without using multiple screens. To address the
challenge of aesthetically depicting both extensive scope and minute detail of
an OR on a single screen without using a patchwork collage of graphics, we
developed a novel approach using a panoramic photograph captured from an
anesthesia provider‘s typical vantage point. We used Director to render the
panoramic background interactive and dynamic. In spite of extensive
computation to allow smooth 360o panning around the OR, image de-warping,
animation and sonification of the panoramic background and projecting
mathematical models up to 3 hours forward in time, the simulation runs in real
time with imperceptible delay on a regular Windows notebook computer. Users
can jump forward and backward in time. Clinicians are currently using the
simulation for training.
An Agent-Based Simulation Study of the Dynamics of
Mobile Viral Advertising
Jiang Wu, Bin Hu, and Shengping Dong
(Huazhong University of Science and Technology)
Abstract:
In the mobile era, mobile advertising is essential and
has been developing very fast. Marketers are eager to turn to mobile viral
advertising for benefiting from initially targeting customers. In this paper,
we propose a computational model to reconstruct the spreading of
advertisements in social networks. Using this computational model as a
test-bed and running a series of virtual experiments, we acquire observations
and implications about how to choose an initial set of people to maximize the
performance of spreading advertisements. Also, we observe and analyze the
impacts of the network structures including topology, size and density and the
initial selected number of targeted people on the dynamics of mobile viral
advertising. The virtual experiments also help us to examine the suitable
policies for combining viral adverting with mass marketing in mobile commerce.
In addition, we run virtual experiments (simulations) in a real mobile-online
social network to validate the model and to provide an example for
practitioners to apply this computational model. In practice, we use the
attributes of people and the interest groups they are members of in social
networks to infer the spreading probability between people.
Optimal Service Channel Reconfiguration Based on
Multi-Agent Simulation
Jin Yan Shao, Ming Xie, Li Xia, Wen Jun Yin,
and Jin Dong (IBM China Research Lab)
Abstract:
Solving the problem of long queues becomes increasingly
urgent in many on-site service outlets. For example, in a bank branch or a
government agency, customers may have to wait for a very long time to be
served. How to optimally reconfigure the capability of service channels in
such outlets is a key for the service providers to improve efficiency and
quality of service. In this paper, we propose a method to optimally configure
service channels at a given service outlet. We integrate customer experience
metrics with cost and profit into a unified objective function for
optimization. Multi-agent simulation is employed to model the stochastic
service processes and customer behavior, and to evaluate the objective
function in optimizing service channel capacity. Some real-life data collected
from bank branches provide significant empirical support to the method and
demonstrate that the presented method is both effective and efficient.
Better Confidence Intervals for Importance
Sampling
Halis Sak and Josef Leydold (Vienna University of
Economics and Business Administration)
Abstract:
It is well known that for highly skewed distributions
the standard method of using the t statistic for the confidence interval for
the mean does not give robust results. This is an important problem for IS as
its final distribution is often skewed due to a heavy tailed weight
distribution. On the poster, we first explain the Hall's transformation to
correct the confidence interval of the mean and then evaluate the performance
of this method for two numerical examples from finance, which have closed form
solutions. Finally, we assess the performance of this method for the credit
risk examples. Our numerical results suggest that Hall's transformation can be
safely used in correcting the confidence intervals of financial simulations.
Decision-Analytic Models for Breast Cancer: Do
Currently Published Models Meet the Requirements of Personalized
Medicine?
Beate Jahn, Nikolai Muehlberger, Johannes Wurm, and Uwe
Siebert (UMIT - Private University for Health Sciences, Medical Informatics
and Technology)
Abstract:
Objective: To give an insight into the structure
and methodology of simulation approaches used for evaluating interventions in
breast-cancer. Research increasingly focuses on personalized strategies in
medicine. Therefore, conventional clinical studies, genomic and proteomic
(–omics) and biomarker studies need to be translated into patient-tailored
prediction rules and treatment decisions. Recommendations for future
comprehensive breast-cancer simulation are derived based on published
simulations and requirements arising from personalized medicine,
Methods: A systematic literature review is performed and information on
study design, simulation framework etc. are extracted. Strengths and
limitations are assesed. Results: The review shows how currently
available models encompass the underlying biologic disease progression,
treatment effects including complications and economic outcomes. We expect
that these models are limited with respect to information from –omics and
biomarker studies. Discrete-event-simulation and agent-based simulation
approaches are discussed. Conclusions: This work provides an essential
basis for further simulation approaches to evaluate personalized breast-cancer
treatment.
