Technical Sessions – Monday July 11

We model and explore search-based advertising auction with multiple slots, advertiser
choice behavior and the popular generalized second-price mechanism.
A Lagrangian-based method is proposed for solving this problem. This method
includes two phases: (1) subgradient algorithm phase; (2) column generation
phase. We present an extension to the method in order to improve the dual multipliers
and accelerate convergence. Simulation results show that the proposed
model is efficient and it shows significant improvement compared to the greedy
algorithm.
� TB-13
Tuesday, 11:00-12:30
Meeting Room 206
Mathematical Programming VI
Stream: Continuous and Non-Smooth Optimization
Invited session
Chair: Luciana Casacio, FEEC, Unicamp, Rua João da Silva Martins,
1192, 13274320, Valinhos, São Paulo, Brazil,
luciana@densis.fee.unicamp.br
1 - Convex Optimization in Sinusoidal Modeling for Audio
Signal Processing
Michelle Daniels, University of California, San Diego, La Jolla,
CA, United States, michelledaniels@ucsd.edu
Sinusoidal modeling is a method for analyzing digital audio signals in which a
signal is decomposed into component sinusoids and residual noise. This work
expands on an analysis process for building such a model which involves detecting
and extracting sinusoids from the original signal. After identifying approximate
frequency, magnitude, and phase for each sinusoid, parameters are
optimized to minimize the energy in the residual. This problem is shown to be
convex in magnitude and phase for known frequency. Results of the optimization
are compared to non-optimized results and are promising.
2 - Robust Design Model for Quality Control in Supply
Chain with Quality Prevention Uncertainty
Cuihua Zhang, Manaement Science and Engineering Dept.,
Northeastern University, School of Business Administration,
China, chzhang@mail.neu.edu.cn
The robust operation of quality control in a multi-product, multi-stage supply
chain consisting of a manufacturer and a buyer is studied. We develop an objective
programming model. And the model is optimized consequently. The
model guarantees coordination of supply chain operation, the maximum profit
of the manufacturer and the buyer, and robustness under quality prevention uncertainty.
The result of a numerical example shows that uncertainty of quality
prevention to some extent cann’t change the quality control strategy .
3 - Optimal Adjustment Algorithm for p Coordinates to Accelerate
the Convergence of Interior Point Methods
Carla Ghidini, Computational & Applied Mathematics, State
University Of Campinas, Campinas, São Paulo, Brazil,
carla@ime.unicamp.br, Aurelio Oliveira, Jair Silva
Optimal adjustment algorithm for p coordinates is a generalization of the optimal
pair adjustment algorithm for linear programming, which, in turn, is based
on von Neumann’s algorithm. Its main advantages are simplicity and fast initial
convergence. To accelerate the convergence of the interior point method few
iterations of the generalized algorithm are applied into the Mehrotra’s heuristic
to determine a good starting solution and in the transition between two preconditioners,
since a hybrid preconditioner approach is used for solving the linear
systems.
4 - On Hybrid Preconditioners for Large-scale Normal
Equations Arising from Interior-point Methods
Luciana Casacio, FEEC, Unicamp, Rua João da Silva Martins,
1192, 13274320, Valinhos, São Paulo, Brazil,
luciana@densis.fee.unicamp.br, Aurelio Oliveira, Carla Ghidini,
Christiano Lyra
The hybrid approach for solving the linear systems arising from interior point
methods uses two preconditioners. A generic one for the first iterations and a
specially tailored one for the final iterations at the end. This work proposes new
approaches for combining both preconditioners, designing new heuristics at the
transition in order to solve large-scale linear programs still faster. Numerical
experiments comparing with previous heuristics exhibit the good performance
of the new approach.
IFORS 2011 - Melbourne TB-14
� TB-14
Tuesday, 11:00-12:30
Meeting Room 207
Memorial Session in Honour of Professor
Alexander Rubinov
Stream: Continuous and Non-Smooth Optimization
Panel session
Chair: Andrew Eberhard, Mathematical and Geospatial Sciences
Dept., RMIT University, GPO Box 2476V, 3001, Melbourne,
Victoria, Australia, andy.eb@rmit.edu.au
Chair: Regina Burachik, School of Mathematics and Statistics,
University of South Australia, Mawson Lakes, 5095, Adelaide, South
Australia, Australia, regina.burachik@unisa.edu.au
Chair: Zari Dzalilov, School of Information Technology and
Mathematical Sciences, University of Ballarat, 1, University Drive,
3353, Ballarat, VIC, Australia, z.dzalilov@ballarat.edu.au
Chair: Adil Bagirov, School of Information Technology &
Mathematical Sciences, University of Ballarat, University Drive,
Mount Helen, P.O. Box 663, 3353, Ballarat, Victoria, Australia,
a.bagirov@ballarat.edu.au
Chair: Alexander Kruger, Graduate School of Information
Technology & Mathematical Sciences, University of Ballarat,
University Drive, Mount Helen, P.O. Box 663, 3353, Ballarat,
Victoria, Australia, a.kruger@ballarat.edu.au
Chair: Musa Mammadov, Graduate School of Information
Technology and Mathematical Sciences, University of Ballarat,
University Drive, Mount Helen, P.O. Box 663, 3353, Ballarat,
Victoria, Australia, m.mammadov@ballarat.edu.au
Chair: Gerhard-Wilhelm Weber, Institute of Applied Mathematics,
Middle East Technical University, ODTÜ, 06531, Ankara, Turkey,
gweber@metu.edu.tr
Chair: John Yearwood, School of InformationTechnology and
Mathematical Sciences, University of Ballarat, Univerity Drive,
Mount Helen, P.O. Box 663, 3353, Ballarat, Victoria, Australia,
j.yearwood@ballarat.edu.au
Chair: Patrick Tobin, Arts and Sciences, Australian Catholic
University, St Patricks Campus, Victoria Pde Fitzroy, 3065,
Melbourne, Victoria, Australia, patrick.tobin@acu.edu.au
Chair: David Yost, Science, Information Technology and
Engineering, University of Ballarat, PO Box 663, 3353, Ballarat,
Vic., Australia, d.yost@ballarat.edu.au
Chair: Xiaoqi Yang, Department of Applied Mathematics, The Hong
Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong,
mayangxq@polyu.edu.hk
Chair: Marco A. López-Cerdá, Statistics and Operations Research,
Alicante University, Ctra. San Vicente de Raspeig s/n, 3071,
Alicante, Spain, marco.antonio@ua.es
Chair: Juan Enrique Martínez-Legaz, Departament d’Economia,
Universitat Autònoma de Barcelona, 08193, Barcelona, Spain,
JuanEnrique.Martinez.Legaz@uab.cat
Chair: Vaithilingam Jeyakumar, Applied Mathematics, University of
New South Wales, School of Mathematics, 2052, Sydney, NSW,
Australia, jeya@maths.unsw.edu.au
Chair: Moshe Sniedovich, Dept. of Mathematics and Statistics,
University of Melbourne, Parkville, 3010, Melbourne, Victoria,
Australia, m.sniedovich@ms.unimelb.edu.au
1 - Memorial Session in Honour of Professor Alexander
Rubinov
Regina Burachik, School of Mathematics and Statistics,
University of South Australia, Mawson Lakes, 5095, Adelaide,
South Australia, Australia, regina.burachik@unisa.edu.au,
Gerhard-Wilhelm Weber, David Yost
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