Technical Sessions – Monday July 11

TD-14 IFORS 2011 - Melbourne
Mawson Lakes, South Australia, Australia,
asef.nazari@unisa.edu.au
The increasing utilization of electricity generated by wind farms in a power
system requires a careful expansion policy for the existing grid. The transmission
expansion planning incorporating uncertainties in load and wind generation
leads to a complex stochastic mixed integer programming problem. The
Cross Entropy method shows promise in solving global optimization problems
regardless of continuity or other assumptions. In this adaptation of the method
to stochastic cases, we sample integer variables using the CE mechanism, and
solve stochastic LPs to obtain matching continuous variables.
2 - Cointegration of Wind Energy from South Australian
Windfarms
Manju Agrawal, Mathematics and Statistics, University of South
Australia, School of Mathematics and Statistics, Mawson Lakes,
5095, Adelaide, South Australia, Australia,
manju.agrawal@unisa.edu.au, John Boland
Volatility of wind energy is a challenge to effecient operation of an electricity
grid. We analyse concurrent data of South Australian wind-farms’ output. Engle
and Granger (1987) demonstrate the importance of cointegration in general
and we apply this concept in the context of Australian windfarms, in particular.
3 - The Ecological Factor in Optimization Models
Marija Cileg, Quantitative Methods in Economy, Faculty of
Economics, Segedinski put 9-11, 24000, Subotica, Serbia,
macileg@yahoo.com, Tibor Kis
The main objective of this paper is to investigate modes of quantifying and
optimizing ecological factors, analyzing this problem from the standpoint of
companies. In the paper we propose a particular method of comparing additional
costs for environment protection and repayments received by companies
that has high importance for the overall profitability. To investigate and solve
the described problem we apply a programming model with fractional objective
function along with appropriate sensitivity analysis. Separate analysis is
devoted to system of limits and to objective function.
4 - Lebesgue Integral Inspired Estimation of 5 Minute Wind
Energy Output
Barbara Ridley, Barbara Hardy Institute, University of South
Australia, School of Mathematics and Statistics, Mawson Lakes,
5095, Adelaide, South Australia, Australia,
barbara.ridley@unisa.edu.au, Jerzy Filar, John Boland
We are investigating the behaviour of total energy output from wind farms using
a Lebesgue integral inspired aggregation of contributions from different energy
bands. This procedure will identify the length of duration of events and also
the waiting time between those events. Our goal is to mathematically model
these processes to forecast the energy from wind farms so that their output can
be reliably estimated in order to enter fully into the competitive electricity market.
Our research is utilising 5 minute data which is the most important time
interval for the Australian electricity market.
� TD-14
Tuesday, 17:00-18:30
Meeting Room 207
Optimization Methods and Stochastic
Calculus in the Financial Sector I
Stream: Continuous and Non-Smooth Optimization
Invited session
Chair: Miroslav Culik, Finance, VSB-TUO, Sokolska tr. 33, 70121,
Ostrava, Czech Republic, miroslav.culik@vsb.cz
Chair: Leonidas Sakalauskas, Operational Research, Institute of
Mathematics & Informatics, Akademijos 4, LT-08663, Vilnius,
Lithuania, sakal@ktl.mii.lt
1 - Option Pricing via Monte Carlo Simulation with Fuzzy
Parameters
64
Tomás Tichý, Department of Finance, Faculty of Economics,
VSB-Technical University Ostrava, Sokolská 33, 701 21,
Ostrava, Czech Republic, tomas.tichy@vsb.cz, Michal Holcapek
During last decades the stochastic simulation approach, both via MC and QMC
has been vastly applied and subsequently analyzed in almost all branches of
science. Since financial quantities, opposed to natural processes, depends on
human activity, their modeling is often very challenging. Many scholars therefore
suggest to specify some parts of financial models by means of fuzzy set
theory. In this contribution the recent knowledge of fuzzy numbers and their
approximation is utilized in order to suggest fuzzy-MC simulation to option
price modeling in terms of fuzzy-random variables.
2 - On the Number of Explanatory Variables of Corporate
Rating Method with Artificial Neural Network
Katsuaki Tanaka, Faculty of Business Administration, Setsunan
University, 17-8 Ikedanakamachi, 572-8508, Neyagawa, Osaka,
Japan, k-tanaka@kjo.setsunan.ac.jp, Hideki Katsuda
Our research objective is to simulate the corporate ratings by rating agency
only with quantitative data using artificial neural networks. The details of rating
agency’s procedure are not disclosed. In rating process, they use not only
quantitative variables in financial statements but also qualitative information
about the company. When we simulate ratings, we have used 12 variables. In
this paper, we delete some variables with low contribution and decide the number
of enough variables based on five years data.Our contribution is to show the
way of reducing a cost burden to get data.
3 - The Stability Investigation of the Three Large Czech
Banks within Z - Metrics Methodology
Petr Gurný, Department of Finance, VSB -TU Ostrava, Sokolska
tr. 33, 70121, Ostrava, Czech Republic, petr.gurny@vsb.cz
The paper is devoted to the investigation of the Czech banks health, which we
can regard as one of the most important tasks in the time of the financial crisis.
The main goal of the paper is an estimation of the future probability of default
(PD) for three key Czech banks. At first the model (built on the basis of the
Z-metrics methodology) for prediction of bank failure will be presented. Afterwards
the relevant financial indicators needed for estimation of the future PD
will be simulated via Lévy processes and their dependencies will be captured
via gaussian copula function.
4 - Cash Management by Two-stage Stochastic Programming
Leonidas Sakalauskas, Operational Research, Institute of
Mathematics & Informatics, Akademijos 4, LT-08663, Vilnius,
Lithuania, sakal@ktl.mii.lt
Problems of cash management are analyzed, that often arise in public, nonprofit-making
or business institutions. Stochastic linear programming formulation
of a firm’s short term financial planning problem is presented using twostage
stochastic model. Two-stage stochastic problems are solved by series of
Monte-Carlo estimators ensuring the solution with admissible accuracy. The
method developed is realized in C++ programming language. Several cases of
application of financial options are investigated.
� TD-15
Tuesday, 17:00-18:30
Meeting Room 208
Holistic Approaches to Military and Security
Modeling
Stream: Military, Defense and Security Applications
Invited session
Chair: Justin Millikan, DSTO Australia, Australia,
justin.millikan@dsto.defence.gov.au
1 - A Study of Issues Involved in using an Explicit Cognitive
Model within an Agent-Based-Model Crowd Scenario
Wayne Johnson, Land Operations Division, Defence Science &
Technology Organisation, 5111, Edinburgh, SA, Australia,
wayne.johnson@dsto.defence.gov.au, Philip Jacques, Martin
Wong
We investigate the feasibility of including simple rule based cognitive models
within Agent-Based-Models (ABMs) in general and the Societal-centric Interactions
Model (ScIMs) project in particular. It will extend an existing published
sociological crowd riot scenario of Jager et al. (2001), in which agents currently
only have a single dimension, aggression-motivation, as a cognitive representation.
The extended cognitive model includes other emotional dimensions to
create a richer emotion, motivation model.