**Seminar on Computer Science and Applied Mathematics**

**PROGRAM**

Knez Mihajlova 36

Fakultet organizacionih nauka, Univerzitet u Beogradu,

Jove Ilica 154

IEEE Chapter Computer Science (CO-16) Belgrade, Republic of Serbia

MI SANU, Knez Mihailova 36, sala 301f

Upravni odbor Matematickog instituta SANU je na nedavnoj sednici doneo odluku da se dosadasnji Seminar za primenjenu matematiku, sada nazove Seminar za racunarstvo i primenjenu matematiku, a u cilju potenciranja znacaja racunarstva kao jedne od oblasti delatnosti Instituta. Istovremeno, Upravni odbor doneo je odluku o osnivanju Odeljenja za racunarstvo i primenjenu matematiku i vezao rad novog odeljenja za rad Seminara za racunarstvo i primenjenu matematiku.

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Petak, 06.09.2013. u 14:15, Sala 301f, MI SANU:
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OBRATITE PAZNJU NA PROMENU TERMINA!!!
Angelo Sifaleras, School of Information Sciences, University of
Macedonia, Thessaloniki, Greece
EXTERIOR POINT SIMPLEX-TYPE ALGORITHMS FOR LINEAR AND
NETWORK OPTIMIZATION PROBLEMS
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Abstract: Two decades of research led to the development of a
number of efficient algorithms that can be classified as exterior
point simplex-type. This type of algorithms can cross over the
infeasible region of the primal (dual) problem and find an optimal
solution reducing the number of iterations needed. The main idea
of exterior point simplex-type algorithms is to compute two
paths/flows. Primal (dual) exterior point simplex-type algorithms
compute one path/flow which is basic but not always primal (dual)
feasible and the other is primal (dual) feasible but not always
basic. The aim of this talk is to present the developments in
exterior point simplex-type algorithms for linear and network
optimization problems, over the recent years. We also present
other approaches that, in a similar way, do not preserve primal or
dual feasibility at each iteration such as the monotonic build-up
Simplex algorithms and the criss-cross methods. Finally, we
discuss about possible future research directions in these
algorithmic approaches.
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Utorak, 10.09.2013. u 14:15h, Sala 301f, MI SANU:
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Petar Jevtic, University of Torino, Italy*

TWO EXAMPLE APPLICATIONS OF THE DIFFERENTIAL EVOLUTION
ALGORITHM IN FINANCE AND INSURANCE

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Abstract: The first example pertains to the field of life
insurance, specifically the modeling of mortality risk. A
cohort-based model which captures the characteristics of a
mortality surface with a parsimonious, continuous-time factor
approach will be presented. The model is implemented on UK data
for the period 1900-2008 and calibration by means of stochastic
search and the Differential Evolution optimization algorithm
proves to yield robust and stable parameters. The second example
pertains to the investment finance domain, specifically exotic
options. A new dimension of calibration risk, given by the
estimation error in model parameters, in the context of exotic
option pricing, is investigated. Looking at two popular option
pricing models and various calibration settings such as error
functionals, dataset features, and optimization routines (local
and global), we analyze the impact of estimation risk on exotic
option prices, by computing confidence intervals via
non-parametric bootstrap re-sampling.
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Utorak, 17.09.2013. u 14:15h, Sala 301f, MI SANU:
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Anton Eremeev, Discrete Optimization Laboratory, Omsk Branch of
Sobolev Institute of Mathematics, Russia*

OPTIMAL RECOMBINATION IN GENETIC ALGORITHMS

Abstract: This talk is a survey of results on complexity of the
optimal recombination problem (ORP), which consists in finding the
best possible offspring as a result of a recombination operator in
a genetic algorithm, given two parent solutions. We consider
efficient reductions of the ORPs, allowing to establish polynomial
solvability or NP-hardness of the ORPs, as well as direct proofs
of hardness results.

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Utorak, 24.09.2013. u 14:15, Sala 301f, MI SANU:
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F. Javier Martin-Campo, Facultad de Ciencias Economicas y
Empresariales, Universidad Complutense de Madrid
MULTI-OBJECTIVE MIXED INTEGER NONLINEAR OPTIMIZATION
MODELS TO SOLVE THE AIRCRAFT CONFLICT DETECTION AND RESOLUTION
PROBLEM BY APPLYING VNS**

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Abstract: Two general Mixed Integer Nonlinear Optimization models
are presented to tackle the Conflict Detection and Resolution
problem in Air Traffic Management. Given a set of flights as well
as their configurations, the aim of the problem consists of
providing a new configuration such that every conflict situation
is avoided, being such an event in which two or more aircraft
violate the minimum safety distances that they must keep during
the flights (5 nm. and 1000 feet as horizontal and vertical
distances, respectively). The first model solves the problem by
performing only horizontal maneuvers (velocity and heading angle
changes) whereas the second performs both, horizontal and vertical
maneuvers at once. The proposed models detect and solve the
conflict situations. They are based on a geometric construction
which involves many trigonometric functions, so that, the model is
constrained by a large set of trigonometric and nonconvex
inequalities. Three different criteria based on goal programming
are presented in order to give some useful information to the air
traffic controllers about the maneuvers to perform. As the
state-of-the-art Mixed Integer Nonlinear Optimization solver,
Minotaur, does not give a solution in almost real time, a VNS
procedure is implemented in order to obtain good solutions in
shorter computing time.
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Joint work with Antonio Alonso-Ayuso, Laureano F. Escudero, Nenad
Mladenovic
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RUKOVODIOCI SEMINARA
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MI SANU
Vera Kovačević-Vujčić
Milan Dražić
FON
Zorica Bogdanovic
Marijana Despotovic-Zrakic
IEEE
Bozidar Radenkovic
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