A Simulation Model to Analyze the Impact of Hole
Size on Putting in Golf
Matulya Bansal and Mark Broadie (Columbia
University)
Abstract:
We develop a model of golfer putting skill and combine
it with physics-based putt trajectory and holeout models to study the impact
of doubling the radius of the hole on the putting performance of professional
and amateur golfers. The putting skill model reflects golfer execution errors,
i.e., that golfers cannot hit the ball at exactly their intended velocity and
direction. A green reading skill model reflects a golfer's inability to
perfectly estimate the slope or contour of the putting surface. The model is
calibrated to professional and amateur putting data. Optimal putting
strategies are computed using stochastic dynamic programming. Quasi-Monte
Carlo and other methods are used to speed up computations. Doubling the hole
radius improves the putting performance of both professional and amateur
golfers, as expected. However, the improvement for amateur golfers is shown to
be relatively larger than for professionals.
Who's Your Tiger? Using Simulation to Optimize the
Lineup of the Detroit Tigers Offense
Jared Michael Davis, Barbara
Fordyce, Matthew Cooper, James Cicala, and Omer Tsimhoni (University of
Michigan)
Abstract:
As part of an undergraduate engineering class project,
a simulation of the Detroit Tigers offense was created to explore potential
changes that would increase number of wins. More specifically, we seek to
determine a lineup for an MLB team, the Detroit Tigers, that would maximize
their potential runs. To answer our ultimate question of whether a manager
actually maximizes runs scores, we compare our results to the Tigers’ 2007
performance. We determine that though the Tigers did not use the ideal line-up
as determined by our model, the lineup they did utilize was moderately robust,
with ours winning 89.6 games versus the actual wins of 88 games. Additionally,
we apply our model to a normative analysis of the Tigers ideal lineup for the
2008 season. This ideal lineup only changes the middle of the batting order
(acceptable by management) and is predicted to win 99 games in the 2008
season.
An Integrated Model for Evaluating Self
Sustainability of Bio-Energy Settlements: Technological, Economical and Social
Aspects
Roberto Revetria (DIPTEM, University of Genoa)
Abstract:
The proposed paper present a generalized model based on
Monte-Carlo simulation able to support the feasibility study by effectively
model the production process, the woods groove and the overall logistics. This
model can be applied to quantitatively identify cost and benefits for an
integrated biomass energetic district and identify, at the same time,
potential and pitfalls that usually reduce the success of an ecologic
initiative. A case study implementing the proposed methodology is presented
and discussed
Towards Applications of Particle Filters in Wildfire
Spread Simulation
Feng Gu and Xiaolin Hu (Georgia State University)
Abstract:
Wildfire propagation is a complex process influenced by
many factors. Simulation models of wildfire spread, such as DEVS-FIRE, are
important tools for studying fire behavior. This paper presents how the
sequential Monte Carlo methods, i.e., particle filters, can work together with
DEVS-FIRE for better simulation and prediction of wildfire. We define an
application framework of particle filters for the problem of wildfire spread
using the DEVS-FIRE model, and discuss several applications. A case study
example is provided and preliminary results are presented.
Models of a Predator-Prey Relationship in a
Closed Habitat
Charles E. Knadler Jr. (none)
Abstract:
The ecological study of the wolf and moose populations
of Isle Royale National Park (USA) is the longest running large mammal
predator/prey study in the world. A discrete event simulation of the park’s
wolf and moose populations is used together with the study’s data to evaluate
four candidate ordinary differential models of predator/prey systems. Using a
least squares technique, the parameters of the four ordinary differential
equation systems are determined for the park’s and the simulation data, then
the models are compared using both objective and subjective criteria.
A Simulation Model for Intensive Piglet
Production Systems
Lluis Miquel Pla-Aragones, Virginia
Flores-Marias, and Sara V. Rodríguez-Sánchez (University of Lleida)
Abstract:
A simulation model representing the dynamics of a sow
farm is presented in contrast with other approaches. To highlight relevant
aspects of the model a real application for planning piglet production is
considered. The main contribution of the model is that sow herd management is
based on batches of sows being in the same reproductive state, as actually is
done in practice. This features allow to measure the discrepancy with other
approaches and comparing different reproductive management strategies in a
more realistic way than by using other quantitative methods. Furthermore, the
implementation in Extend allows potential users to perform efficiently
different kinds of analyses tracking variables of their own interest.
