Technical Sessions – Monday July 11

TA-15 IFORS 2011 - Melbourne
4 - The Back Propagation Algorithm Using the Bi-
Hyperbolic Activation Function
Geraldo Miguez, COPPE / PESC, Universidade Federal do Rio
de Janeiro, Brazil, R Mariz e Barros, 652/502, 20270-002, Rio de
Janeiro, RJ, Brazil, geraldomiguez@yahoo.com, Nelson
Maculan Filho, Adilson Elias Xavier
Back propagation algorithm is one of the most used tools for training artificial
neural networks. However, in some practical applications it may be very
slow. To allow a broader use, many techniques were discussed to speed up
its performance. This paper presents a new strategy based in the use of the
Bi-hyperbolic function that offers more flexibility and a faster evaluation time.
The efficiency and the discrimination capacity of the proposed methodology are
shown through a set of computational experiments with traditional problems of
the literature.
� TA-15
Tuesday, 9:00-10:30
Meeting Room 208
Weapon Systems Analysis
Stream: Military, Defense and Security Applications
Invited session
Chair: Won Joon Jang, Defense Industry Team, Korea Institute for
Industrial Economics and Trade, Hoegi-ro 66, Dongdaemun-gu,
133-771, Seoul, Korea, Republic Of, wjjang47@snu.ac.kr
1 - The RAM Goal Setting Model with the use of OMS/MP
Analysis for the Weapon System Development
Won Joon Jang, Defense Industry Team, Korea Institute for
Industrial Economics and Trade, Hoegi-ro 66, Dongdaemun-gu,
133-771, Seoul, Korea, Republic Of, wjjang47@snu.ac.kr,
Kyung Yong Kim
The paper presents the RAM Goal Setting model with the basis of
wartime/peacetime OMS/MP results and its Total Down Time factors for the
development of the weapon system. Based on both previous studies, the peer
review results and various proven techniques, it presents the RAM goal setting
model with its real implementation case study result. It verifies with ALPHA
simulation tools, too. It could provide the basis of its development of weapon
system and it could contribute both to enhance its operational availability and
to reduce the Total Ownership Cost during its whole service life time.
2 - Integrated Survivability for ADF Land Platforms
Patrick Taliana, Defence, DSTO, PO Box 1500, 5111,
Edinburgh, South Australia, Australia,
patrick.taliana@dsto.defence.gov.au
Land platforms may be engaged by a wide variety of threats which can be difficult
to predict and are constantly evolving. There are numerous technologies
that have the potential to improve the probability of survival of land platforms.
Deciding what mix of technologies maximises probability of survival is a non
trivial task. Many researchers have adopted the Classical Survivability Onion
model to represent the integrated survivability problem space. This report will
outline the limitations of the classical Onion model and preset an alternative
Integrated Survivability strategy called DESIST.
3 - Network Optimization Models for Resource Allocation
in Developing Military Countermeasures
Boaz Golany, Industrial Engineering & Management, Technion -
Israel Institute of Technology, Technion City, 32000, Haifa,
Israel, golany@ie.technion.ac.il, Moshe Kress, Michal Penn,
Uriel G. Rothblum
The paper considers an arms race where an attacker develops new weapons and
a defender develops countermeasures that mitigate the effects of the weapons.
We address the defender’s decision problem: given limited resources, which
countermeasures to develop and how much to invest in their development so as
to minimize the damage caused by the attacker’s weapons over a certain horizon.
The problem is formulated as constrained shortest path model and variants
thereof. The potential applicability and robustness of this approach with respect
to various scenarios is demonstrated.
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� TA-16
Tuesday, 9:00-10:30
Meeting Room 209
Metaheuristics for Scheduling in
Manufacturing
Stream: Scheduling
Invited session
Chair: Frédéric Dugardin, LOSI, University of Technology of Troyes,
12, rue Marie Curie, 10010, Troyes, France, frederic.dugardin@utt.fr
Chair: Farouk Yalaoui, Institut Charles Delaunay, ICD LOSI,
University of Technology of Troyes, 12, Rue Marie Curie BP 2060,
10000, Troyes, France, farouk.yalaoui@utt.fr
Chair: Lionel Amodeo, Charles Delaunay Institute, University of
Technology of Troyes, 12 Rue Marie Curie BP2060, 10000, Troyes,
France, lionel.amodeo@utt.fr
1 - Fuzzy-Lorenz Algorithm to Solve Multi-objective Reentrant
Scheduling Problem
Frédéric Dugardin, LOSI, University of Technology of Troyes,
12, rue Marie Curie, 10010, Troyes, France,
frederic.dugardin@utt.fr, Farouk Yalaoui, Lionel Amodeo
This paper deals with the multi-objective scheduling of a reentrant hybrid flowshop.
In this study the two different objectives are the makespan and the sum
of the total tardiness minimization. The system is composed of several stages
which involves several parallel identical machines. Moreover each task must
be processed more than once at each stage. This problem is solved using the
Lorenz dominance which involves more parameters than the Pareto one. In this
study we use Fuzzy logic Controller to adapt the value of these parameters to
improve the results of the previous algorithm. This algorithm is tested on several
instances from the literature and compared with some of the best known
algorithms.
2 - New Heuristic for Solving the Minimization of Tool
Switches Problem
Horacio Yanasse, LAC, INPE, Av. dos Astronautas 1758, CP 515
- INPE/CTE, 12227-010, São José dos Campos, SP, Brazil,
horacio@lac.inpe.br, Edson Senne, Rita de Cássia Meneses
Rodrigues
In the minimization of tool switches problem we seek a sequence to process a
set of jobs so that the number of tool switches required is minimized. In this
work we present a new heuristic for solving this problem based on generating
a surrogate potentially smaller sized instance of MTSP, whose solution can be
used to build a solution to the original instance. To obtain this solution to the
MTSP we propose a heuristic based on partial ordered job sequences. Computational
test results are presented showing that the proposed heuristic has an
improved performance compared with previous proposed schemes.
3 - A Fuzzy Logic Controller to Solve a Scheduling Problem
Naim Yalaoui, Institut Charles Delauney, Université de
Technologie de Troyes, 12, Rue Marie Curie, 10000, Troyes,
France, naim.yalaoui@utt.fr, Lionel Amodeo, Farouk Yalaoui,
Halim Mahdi
In this paper, we deal with a specific scheduling problem. This one is an hybrid
flow shop problem. The jobs are processed on parallel unknown machines in
each stage. Those are pre assigned to the machines. In some stages, the jobs are
processed on a fictive machine. The objective function is to minimize the total
tardiness. We propose an exact method based on a complete enumeration and
different metaheuristics such as a genetic algorithm, genetic algorithm under
fuzzy logic-control, a particle swarm algorithm and particle swarm algorithm
under fuzzy logic-control. The tests examples were generated using a specific
protocol. The obtained results are very interesting.