Technical Sessions – Monday July 11

1 - Accommodation Arrangements of Ships and Craft VIA
Quadratic Assignment Problem Applying GRASP and
VNS Meta-heuristics Methods
Valdir Melo, Production Engineering, Federal University of Rio
de Janeiro - UFRJ, Ilha do Fundão - Cidade Universitária, Centro
de Tecnologia - Bloco F - Sala 105, 21941-972, Rio de Janeiro,
Brazil, vmelo@pep.ufrj.br, Nair Abreu, Richard David
Schachter, Eliane Maria Loiola
This work presents an improvement for a ’Ships Deck Accommodation Arrangements’
software, for automated graphical space allocations, to aid marine
designers. Accommodations are selected and sized via interface and their optimum
allocation is determined by a QAP model, using a hybrid meta-heuristic,
for quicker feasible solutions and, was introduced in this work, two penalty
functions to reduce symmetry and concentrate unit squares that compose an
accommodation. This improved allocations, now considering their relative position
to the ship, if forward, aft or sideways.
2 - Power Efficient Broadcast Routing in Static Wireless
Ad-Hoc Network Using Swarm Intelligence
S. Mehdi Hashemi, Computer Science, Amirkabir University of
Technology, Hafez Avenue, Tehran, Iran, Islamic Republic Of,
hashemi@aut.ac.ir, Ahmad Moradi, Mohsen Rezapour
Given a network with an identified source node, any broadcast routing is considered
as a directed tree rooted at the source node and spans all nodes. As the
problem is NP-Hard, we try to tackle it heuristically. First we propose an efficient
PSO based algorithm with different coding schema. Then we present the
second algorithm combining the global search of the first algorithm with a local
search strategy based on noising methods. Comprehensive experimental study
is devoted to compare the behavior of the proposed algorithm and to show its
priority over the best known previous results.
3 - Extracting Rules from Genetic Algorithms to Electrical
Energy Classification
Pedro Steiner Neto, Business, Federal University at Paraná, R.
Pe. Anchieta, 1231, 80730-000, Curitiba, Pr., Brazil,
pedrosteiner@ufpr.br, Anderson Roges Teixeira Goes, Maria
Teresinha Arns Steiner
The methodology presented in this work uses Genetic Algorithms in the rules
extraction in order to analyse the Electrical Energy Quality (EEQ). In order
to do that, it were used patterns and their classes which are related to the responsibilities
related to the voltage sag: equipment manufacturer; consumer or
electrical energy concessionaries, as it was done by Casteren et al., 2005.
� FB-04
Friday, 13:15-14:45
Meeting Room 103
Optimization in Bulk Goods Supply Chains
Stream: Supply Chain Management
Invited session
Chair: Natashia Boland, School of Mathematical and Physical
Sciences, The University of Newcastle, 2308, Callaghan, NSW,
Australia, natashia.boland@newcastle.edu.au
Chair: Gaurav Singh, Mathematics, Informatics & Statistics,
Commonwealth Scientific and Industrial Research Organisation
(CSIRO), Private Bag 33, 3169, South Clayton, Victoria, Australia,
Gaurav.Singh@csiro.au
1 - A Branch-price-and-cut Algorithm for a Maritime Inventory
Routing Problem
Henrik Andersson, Department of Industrial Economics and
Technology Management, Norwegian University of Science and
Technology, Gløshaugen, Alfred Getz vei 3, NO-7491,
Trondheim, Norway, Henrik.Andersson@iot.ntnu.no, Marielle
Christiansen, Guy Desaulniers
A maritime inventory routing problem from the liquefied natural gas (LNG)
industry is presented. The LNG is produced at liquefaction plants and transported
using a heterogeneous fleet of ship to regasification terminals where it
is sold. Both plants and terminals have limited storage capacities and production
and sale are variables. A branch-price-and-cut algorithm is developed for
the problem where a ship’s movement is described using voyages. The valid inequalities
explore the heterogeneity of the fleet, only full loading and unloading
of ship tanks and the variable production and sale.
IFORS 2011 - Melbourne FB-05
2 - Rail Schedule Optimisation in the Hunter Valley Coal
Chain
Andreas Ernst, Mathematics, Informatics and Statistics, CSIRO,
Gate 5, Normanby Road, 3168, Clayton, Vic, Australia,
Andreas.Ernst@csiro.au, Gaurav Singh, David Sier
The Hunter Valley Coal Chain is the largest coal export operation in the world
with total exports of more than 100 mil tonnes in 2010. It contains 35 mines
with over 1000 km of rail track. The movement of coal is scheduled by the
HVCC Coordinator (HVCCC). We present models and algorithms for a decision
support tool developed to assist the HVCCC planners create optimal rail
schedules. The tool greatly reduces the time taken to develop these schedules,
allowing the planners to test the outcomes of various railing strategies before
finalising the schedule. We also present computational results.
3 - Optimisation Tool for Medium-term Planning at Rio
Tinto Iron Ore
Gaurav Singh, Mathematics, Informatics & Statistics,
Commonwealth Scientific and Industrial Research Organisation
(CSIRO), Private Bag 33, 3169, South Clayton, Victoria,
Australia, Gaurav.Singh@csiro.au, Andreas Ernst, Rodolfo
Garcia-Flores
In supply chains, medium term plans are used to maximise throughput, identify
bottlenecks, production and maintenance planning. This plan needs to observe
constraints like maintenance requirements, production plans, and capacities of
fleet, dumping, loading and stockyard. The model also needs to consider the
grade qualities, which introduces a non-linear objective as the quality depends
on the mixing ratio of ore from different sources. We present an optimisation
tool developed to assist the Rio Tinto planners create optimal plans and has
greatly reduced the time taken to develop such plans.
4 - Maintenance Scheduling for the Hunter Valley Coal
Chain
Thomas Kalinowski, University of Newcastle, Australia,
thomas.kalinowski@newcastle.edu.au, Natashia Boland, Hamish
Waterer, Lanbo Zheng
We present a problem motivated by the annual maintenance planning process
for the Hunter Valley Coal Chain which constitutes mining companies, rail
operators, rail track owners and terminal operators. By carefully aligning necessary
maintenance on different infrastructure parts capacity losses can be reduced
significantly. We describe a dynamic network flow model for optimizing
this alignment, discuss some LP based heuristic approaches to solving the
model, and present computational results on random and real world instances.
� FB-05
Friday, 13:15-14:45
Meeting Room 104
OR and Sports 1
Stream: OR and Sports
Invited session
Chair: Tristan Barnett, School of Mathematics and Statistics,
University of South Australia, 1/11 Findon St, Hawthorn, 3122,
Melbourne, Victoria, Australia, strategicgames@hotmail.com
1 - Markov Modelling in Hierarchical Games with Reference
to Tennis
Andrei Loukianov, School of Mathematics and Statistics,
University of South Australia, 307/23 King William Street, 5000,
Adelaide, South Australia, Australia,
andrei.loukianov@postgrads.unisa.edu.au, Vladimir Ejov
We propose a model, analytical approach and numerical technique to determine
a winning probability of ‘a point played’. The fundamental idea is to
include sport specific competition situations in the stochastic analysis of hierarchical
games. Our model is effectively a perturbed Markov Chain equipped
with Bayesian player performance profiles.
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