Technical Sessions – Monday July 11

� MA-07
Monday, 11:30-13:00
Meeting Room 106
Cutting and Packing 1
Stream: Cutting and Packing
Invited session
Chair: A. Miguel Gomes, Faculty of Engineering / INESC Porto,
University of Porto, Rua Dr. Roberto Frias s/n, 4200-465, Porto,
Portugal, agomes@fe.up.pt
1 - Modified KOMBI to Reduce the Different Patterns in
Cutting Stock Problems
Horacio Yanasse, LAC, INPE, Av. dos Astronautas 1758, CP 515
- INPE/CTE, 12227-010, São José dos Campos, SP, Brazil,
horacio@lac.inpe.br, Kelly Poldi
Reducing the number of cutting patterns in a cutting stock problem may be of
interest in some productive systems. In this work we propose a simple variation
of KOMBI, a pattern reduction method suggested previously in the literature.
The improved performance of this variation, compared with the previous one,
is illustrated with computational test results with one dimensional cutting stock
instances. Extensions of the modified KOMBI that balance the reduction of cutting
patterns with an increase in the number of objects cut are also presented.
2 - A Biased Random Key Genetic Algorithm for the Threedimensional
Bin Packing Problem
José Fernando Gonçalves, LIAAD, Faculdade de Economia,
Universidade do Porto, Rua Dr. Roberto Frias, s/n, 4200-464,
Porto, Portugal, jfgoncal@fep.up.pt
In this paper we propose a biased random key genetic algorithm for the threedimensional
bin packing problem. For each GA chromosome we construct a
solution based on a maximal-space heuristic which packs the boxes according
to the order supplied by chromosome. Next an improvement procedure is
applied to the solution. Computational tests are presented using available instances
taken from the literature. The results validate quality of the solutions
and the approach. Supported by Fundação para a Ciência e Tecnologia (FCT)
project PTDC/GES/72244/2006.
3 - A Hierarchical Approach to the Circle Covering Problem
A. Miguel Gomes, Faculty of Engineering / INESC Porto,
University of Porto, Rua Dr. Roberto Frias s/n, 4200-465, Porto,
Portugal, agomes@fe.up.pt, Pedro Rocha, Jose Fernando
Oliveira
Covering problems aim to cover a certain complex region with a set of simpler
geometric forms. The objective is to minimize the number of covering objects
while making the best approximation to the initial complex region. A particular
case of a problem of this kind is the circle covering problem (CCP), where the
goal is to minimize the radius of circles that can fully cover a given region, with
a fixed number of identical circles. The specific problem approached in this
work is to cover a multi-connected region represented by a complex polygon
(i.e., irregular polygons with holes). This work presents a hierarchical approach
to enclosing a given irregular geometrical form, using non-uniform circular enclosures.
Preliminary computational experiments with complex polygons taken
from nesting datasets show promising results. (Partially supported by Fundação
para a Ciência e Tecnologia (FCT) — Project PTDC/EME-GIN/105163/2008
— EaGLeNest).
4 - An Improved Problem Generator for the Twodimensional
Rectangular Cutting and Packing Problem
Jose Fernando Oliveira, Faculty of Engineering / INESC Porto,
Universidade do Porto, Rua Dr. Roberto Frias, 4200-465, Porto,
Portugal, jfo@fe.up.pt, A. Miguel Gomes, Gerhard Wäscher
We present an improved problem generator for the two-dimensional rectangular
cutting and packing problem. This problem generator addresses all basic
types of the 2D rectangular problem, according to Waescher et al. typology,
and the advantages in relation to the existent generators are discussed and highlighted.
(Partially supported by FCT — Project PTDC/EIA-CCO/115878/2009
- CPackBenchFrame)
IFORS 2011 - Melbourne MA-09
� MA-08
Monday, 11:30-13:00
Meeting Room 107
Tutorial
Stream: Bioinformatics
Invited session
Chair: Ming-Ying Leung, The University of Texas at El Paso, TX
79968-0514, El Paso, United States, mleung@utep.edu
1 - Graph Approaches to Genome Reading
Jacek Blazewicz, Instytut Informatyki, Politechnika Poznanska,
ul.Piotrowo 2, 60-965, Poznan, Poland,
jblazewicz@cs.put.poznan.pl
In the talk we will present the operational research approaches to the DNA
and RNA chain reading. First, the DNA sequencing problem will be analyzed.
Based on it, the algorithms solving the DNA assembling problem, involving
454 sequencers, will be characterized. An impact of this approach on the graph
theory itself will be also presented. Later, RNA Partial Degradation Problem
will be described. We will give its mathematical formulation and present its
complexity status as well as algorithms for its solution.
� MA-09
Monday, 11:30-13:00
Meeting Room 108
Stochastic Demand & Dynamic Travel Time
Stream: Vehicle Routing
Invited session
Chair: Richard Eglese, The Management School, Lancaster
University, Department of Management Science, LA1 4YX,
Lancaster, Lancashire, United Kingdom, R.Eglese@lancaster.ac.uk
1 - Solving the VRP with Stochastic Demands using Distributed
and Parallel Computing
Javier Faulin, Department of Statistics and OR, Public University
of Navarre, Los Magnolios Builing. First floor, Campus
Arrosadia, 31006, Pamplona, Navarra, Spain,
javier.faulin@unavarra.es, Angel A. Juan, Josep Jorba, Scott
Grasman
This work focuses on the VRP with Stochastic Demands (VRPSD) presenting
an algorithm that combines parallel computing, heuristics and Monte Carlo
simulation. Thus, for a given VRPSD instance, the algorithm considers different
levels of the safety stocks or scenarios. Then, it solves each scenario
concurrently by integrating Monte Carlo simulation with the Clarke & Wright
heuristic. The resulting parallel solutions are compared and the one with the
minimum total costs is selected. Finally, the paper also discuses some future
work regarding the use of distributed computing approaches for VRP.
2 - The Vehicle Routing Problem with Stochastic Demand:
A Sample Average Approximation Method for Assigning
Time Windows
Remy Spliet, Econometric Institute, Erasmus University
Rotterdam, Burgemeester Oudlaan 50, 3000DR, Rotterdam,
Netherlands, Spliet@ese.eur.nl
In our research we consider a vehicle routing problem in which time windows
have to be assigned for each location before demand is known. Next, demand
is revealed and a routing schedule has to be constructed, adhering to the time
windows. This problem is encountered frequently in retail chains. We solve
this problem by using a sample average approximation approach. We find a
solution to the resulting deterministic problem by using a column generation
algorithm.
3 - A Solution Approach for Routing with Time-dependent
Travel Times
Fabien Tricoire, Department of Business Administration,
University of Vienna, Chair for Production and Operations
Management, Brünner Straße 72, 1210, Vienna, Austria,
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