[PDF] ALIO Back Matter

SD20
2 - Optimal Map Segmentation for Vehicle Routing and Other Resource
Allocation Problems
John Carlsson, Assistant Professor, University of Minnesota,
111 Church Street SE, Department of Mechanical Engineering,
Minneapolis, MN, 55455, United States of America,
jgc@me.umn.edu
Segmenting a given geographic region into pieces is a problem that arises in many
contexts, such as congressional redistricting and vehicle routing. Here we describe
several geometry-based algorithms for partitioning a region into pieces optimally
when the objective is to balance the loads of vehicles in a service region.
3 - Dynamic Vehicle Routing Under Congestion using
Real-time ITS Information
Ratna Babu Chinnam, Associate Professor, Wayne State University,
4815 Fourth St., Detroit, MI, 48202, United States of America,
R_Chinnam@wayne.edu, Alper Murat, Ali R. Guner
Travel time delays and variability, attributable to network congestion, are impacting
the efficiency of JIT logistics operations. We propose a stochastic programming
algorithm for dynamic routing of vehicles in stochastic dynamic networks subject to
recurrent (i.e. rush hour) and non-recurrent (i.e. incident) congestion. We also
propose integration of an incident induced delay model to our algorithm. The
algorithm is tested in a Michigan road network using historical data from the MITS
Center.
4 - Metaheuristics for the Waste Collection VRP with Time Windows
and Multiple Disposal Facilities
John Beasley, Brunel University, Mathematical Sciences, Uxbridge,
UB8 3PH, United Kingdom, John.Beasley@brunel.ac.uk
Vehicles go out from the depot and collect waste from customers, emptying
themselves at the waste disposal sites as and when necessary. A nearest neighbour
approach is used to obtain an initial solution. We improve this solution using an
approach based on neighbour sets. Computational results are presented for problems
involving up to 2100 customers using tabu search, variable neighbourhood search
and variable neighbourhood tabu search.
ALIO / INFORMS International – 2010
48
■ SD20
Aula 382- Third Floor
Cutting and Packing 2
Cluster: 7th ESICUP Meeting
Invited Session
Chair: A. Miguel Gomes, Faculdade de Engenharia da Universidade do
Porto, Rua Dr. Roberto Frias, s/n, Porto, 4200-465, Portugal,
agomes@fe.up.pt
1 - Strip Packing: What Can We Learn from Project Scheduling?
Sam D. Allen, University of Nottingham, School of Computer
Science and IT, Jubilee Campus, Nottingham, United Kingdom,
sda@Cs.Nott.AC.UK, Sven Groenemeyer, Edmund K. Burke,
Graham Kendall
In this talk we re-examine the intrinsic similarities between the formulation of the
higher-dimensional strip-packing problem and the resource-constrained project
scheduling problem as highlighted by Hartmann in 2000. We discuss approaches to
both problems and present previous results based on each problem. We will then
conclude with some transformations of heuristics intended for each problem in
order to tackle the alternative problem, and discuss their effectiveness in each
domain.
2 - Geometric Operations Involving Cutting-stock Problem Through
CAD Application
Cliceres Mack Dal Bianco, Universidade Federal de Santa Maria -
UFSM, UFSM Prédio 07 S 305 Centro de Tecnologi, Rua Adriano
Chaves 270, apto 270 - Camob, Santa Maria, 97105010, Brazil,
cliceres@gmail.com, Alexandre Dias Silva
Systems to solve Cutting-stock Problems involve geometric operations such as:
rotation and verifications of overlapping. To eliminate the need of implementing
complex algorithms, this work presents as alternative for the 2D rectangular
guillotine cutting, the development of these operations the use of resources
available in CAD systems. The feasibility of implementing the technique was
demonstrated in AutoCAD, through the utilization of drawing functions in
programs developed in AutoLISP.
3 - Rect-TOPOS: A Constructive Heuristic for the Rectangle Packing
Area Minimization Problem
A. Miguel Gomes, Faculdade de Engenharia da Universidade do
Porto, Rua Dr. Roberto Frias, s/n, Porto, 4200-465, Portugal,
agomes@fe.up.pt, Marisa Oliveira, Eduarda Pinto Ferreira
To solve the rectangle packing area minimization problem we propose a variant of
the TOPOS algorithm. In our adaptation, the layout is build by successively adding a
new rectilinear piece to a partial solution while minimizing the enclosing
rectangular area. Several criteria to choose the next piece and its orientation are
proposed and compared. To evaluate and compare partial solutions different
objective functions were used. Supported by FCT project PTDC/GES/ 72244/2006.
4 - A Tree-search Algorithm for the Two-dimensional Rectangular
Strip Packing Problem
José F. Oliveira, Universidade do Porto, Faculdade de Engenharia /
INESC Porto, Rua Dr. Roberto Frias, Porto, Portugal, jfo@fe.up.pt,
Maria Antónia Carravilla, André Carqueja
In this talk a tree-search algorithm for the two-dimensional rectangular strip
packing problem will be presented. This algorithm is based on a MIP model, where
the binary variables stand for the relative position of the rectangles among each
other. The variables are progressively fixed along the search, while bounds are
produced and updated by the resolution of relaxations of the model. Computational
results obtained with benchmark instances for this class of problems are presented.