Technical Sessions – Monday July 11

Ben-Ishay, Rosanna Grassi, Sagi Hilleli, Ephraim Korach,
Silvana Stefani, Anna Torriero
The OS problem is given hypergraph (V,S) where V set of elements, S collection
of subsets (clusters) of V and given complete weighted graph G=(V,E),
find clustering spanning tree T with minimum weight where each cluster in S
induces star in T. We use the known polynomial algorithm for the OS as tool
for determining the centralities of nodes. As first step to test whether various
instances have feasible solutions. We developed probabilistic lower bound for
inexistence of feasible solution. The OS problem can be applied successfully
to the analysis of the board director’s network.
3 - A Parallel Branch & Bound for the Capacitated Centred
Clustering Problem
Marcos José Negreiros, MESTRADO PROFISSIONAL EM
COMPUTAÇÃO, UNIVERSIDADE ESTADUAL DO CEARÁ,
Av Paranjana, 1700 - Campus do Itaperi, 60740-000, Fortaleza,
CEARÁ, Brazil, negreiro@graphvs.com.br, Augusto Palhano,
Pablo Luis Fernandes
The Capacitated Centred Clustering Problem is a problem that considers a number
of customers with their location and demand attributes, and a fixed cost to
open a cluster of customers. The problem wants to minimize both fixed and
variable cost of opening and assingning customers to clusters with minimum
internal variance in the clusters. This work shows a new parallel branch and
bound strategy, which is non recursive, that uses new lower bounds and upperbounds
for the CCCP that can solve and prove optimality to some moderate
sized instances selected from the pertinent literature.
4 - Cut-and-branch versus Branch-and-cut for protecting
sensitive cells when publishing statistical tables
Juan José Salazar González, Estadística e Investigación
Operativa, Universidad de La Laguna (Tenerife), Av. Astrofísico
Francisco Sánchez, s/n, Facultad de Matemáticas, 38271, La
Laguna, Tenerife, Spain, jjsalaza@ull.es
This paper discusses several techniques to apply Cell Suppression Methodology
to protect private information when publishing tabular data. All techniques
are exact algorithms to find optimal suppression patterns, but they can also be
used as heuristic approaches to find good suppression patterns. We show advantages
and disadvantages of a cut-and-branch algorithm when compared to
a branch-and-cut algorithm, and shows computational results on a set of real
world instances. The computer implementation has been done using only free
and open-source libraries.
� HB-08
Thursday, 11:00-12:30
Meeting Room 107
Dynamic Programming Applications II
Stream: Dynamic Programming
Invited session
Chair: Thomas Archibald, Business School, University of Edinburgh,
29 Buccleuch Place, EH8 9JS, Edinburgh, United Kingdom,
T.Archibald@ed.ac.uk
1 - Mitigating Inequities in Organ Allocation via Revised
Health Reporting Frequencies
Lisa Maillart, University of Pittsburgh, United States,
maillart@pitt.edu
In the US, the minimum frequency with which patients awaiting liver transplantation
must report their current health (i.e., MELD score) depends on their
last reported score. Hence, patients can conceal changes in their MELD scores
and "game’ the system. Using a Markov decision process model parameterized
by clinical data, we examine the degree to which an individual patient
can benefit from this flexibility, and investigate revised updating frequency requirements.
Our results suggest that the current updating requirements are too
stringent (lenient) for the healthier (sicker) patients.
2 - Dynamic Programming for Hot Rolling Operational Optimization
Li Chen, The Logistics Institute, Northeastern University,
Shenyang, Liaoning province, China, chenlisky2000@126.com,
Lixin Tang
IFORS 2011 - Melbourne HB-09
In this paper the hot rolling operational optimization problem is formalized
as a nonlinear mathematical model. It takes getting good shape as the objective
function. But sometimes the static setting rolling operational model can’t
achieve the shape control purposes, in other words we can’t get the target strip
crown and flatness. In order to solve this problem, dynamic programming is
used to adjust the initial rolling operation by mean of adjusting the reduction.
The experiment results show that this method can achieve the shape coordinated
control purposes.
3 - Dynamic Routing of Time-Sensitive Air Cargo using
Real-Time Information
Alper Murat, Industrial and Manufacturing Engineering, Wayne
State University, 4815 Fourth Street, 48202, Detroit, MI, United
States, amurat@wayne.edu, Farshid Azadian, Ratna Babu
Chinnam
Route planning of time-sensitive air-cargo is becoming more important with
growing air-network congestion and delays. We consider dynamic routing of
a time-sensitive air-cargo in presence of real-time and historical information
regarding flight availability, departure delays and travel times. A novel Markov
decision model is formulated and solved with backward dynamic programming.
Through synthetic experiments and case studies, we demonstrate that
dynamic routing with real-time information can improve delivery reliability
and reduce expected cost.
4 - Dynamic Portfolio Selection with Maximum Risk Level
Mei Yu, University of International Business and Economics,
China, yumei@amss.ac.cn
In this paper, a new dynamic portfolio selection model is established. Different
from original consideration that risk is defined as the variance of terminal
wealth, the total risk is defined as the average of the sum of maximum absolute
deviation of all assets in all periods. At the same time, noticing that the risk
during the period is so high that the investor may go bankrupt, a maximum risk
level is given to control risk in every period. By introducing an auxiliary problem,
the optimal strategy is deduced via the dynamic programming method.
� HB-09
Thursday, 11:00-12:30
Meeting Room 108
Humanitarian Logistics
Stream: Emergency Evacuation and Response
Invited session
Chair: Irina Dolinskaya, Industrial Engineering and Management
Sciences, Northwestern University, 2145 Sheridan Road, M235,
60208, Evanston, IL, United States, dolira@northwestern.edu
1 - A Transshipment Model for Redistribution and Relocation
of Relief Items under Uncertainty in Humanitarian
Operations
Beate Rottkemper, Institute for Operations Research and
Information Systems, Hamburg University of Technology,
Schwarzenbergstr. 95, 21073, Hamburg, Germany,
beate.rottkemper@tu-harburg.de, Kathrin Fischer
The question how to react to sudden demand peaks, e.g. an epidemical spread,
or to supply lacks during aid operations is considered. These situations require
quick delivery of relief goods. Transferring supply from adjacent areas might
cause new shortages, hence an integrated solution approach is required, taking
possible future developments in account. Therefore, a new transshipment
model for stock relocation under uncertainty is formulated. Progressively increasing
penalty costs for unsatisfied demand are used to balance the objectives
of minimizing unsatisfied demand and operational costs.
2 - Humanitarian-logistics Response through the Use of
Mobile Technologies and Optimization Models
Marco Serrato, Graduate, Consulting & Continuing Education
Programs, Tecnologico de Monterrey, Camino a Jesus del Monte
s/n, Col Jesus del Monte, 58350, Morelia, Michoacan, Mexico,
mserrato@itesm.mx, Roman Murillo
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