SIMULATED ANNEALING – ADVANCES, APPLICATIONS AND HYBRIDIZATIONS pot

SIMULATED ANNEALING –
ADVANCES, APPLICATIONS
AND HYBRIDIZATIONS

Edited by Marcos de Sales Guerra Tsuzuki








Simulated Annealing – Advances, Applications and Hybridizations

Edited by Marcos de Sales Guerra Tsuzuki

Contributors
T.C. Martins, A.K. Sato, M.S.G. Tsuzuki, Felix Martinez-Rios, Juan Frausto-Solis, Masayuki
Ohzeki, Dursun Üstündag, Mehmet Cevri, Cristhian A. Aguilera, Mario A. Ramos, Angel D.
Sappa, Yann-Chang Huang, Huo-Ching Sun, Kun-Yuan Huang, Hisafumi Kokubugata, Yuji
Shimazaki, Shuichi Matsumoto, Hironao Kawashima, Tatsuru Daimon, F. Charrua Santos,
Francisco Brojo, Pedro M. Vilarinho, Edo D’Agaro, Sergio Ledesma, Jose Ruiz, Guadalupe
Garcia, Tiago Oliveira Weber, Wilhelmus A. M. Van Noije, Xiaorong Xie, Makoto Yasuda

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First published August, 2012
Printed in Croatia

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Additional hard copies can be obtained from


Simulated Annealing – Advances, Applications and Hybridizations,
Edited by Marcos de Sales Guerra Tsuzuki
p. cm.
ISBN 978-953-51-0710-1

Contents

Preface IX
Section 1 Advances in SA 1
Chapter 1 Adaptive Neighborhood Heuristics
for Simulated Annealing over Continuous Variables 3
T.C. Martins, A.K. Sato and M.S.G. Tsuzuki
Chapter 2 A Simulated Annealing Algorithm for
the Satisfiability Problem Using Dynamic Markov Chains
with Linear Regression Equilibrium 21
Felix Martinez-Rios and Juan Frausto-Solis
Chapter 3 Optimization by Use of Nature
in Physics Beyond Classical Simulated Annealing 41
Masayuki Ohzeki
Section 2 SA Applications 65
Chapter 4 Bayesian Recovery of
Sinusoids with Simulated Annealing 67
Dursun Üstündag and Mehmet Cevri
Chapter 5 Simulated Annealing: A Novel Application
of Image Processing in the Wood Area 91
Cristhian A. Aguilera, Mario A. Ramos and Angel D. Sappa
Chapter 6 Applications of Simulated Annealing-Based
Approaches to Electric Power Systems 105

Yann-Chang Huang, Huo-Ching Sun and Kun-Yuan Huang
Chapter 7 Improvements in Simulated Quenching Method
for Vehicle Routing Problem with Time Windows
by Using Search History and Devising Means
for Reducing the Number of Vehicles 129
Hisafumi Kokubugata, Yuji Shimazaki, Shuichi Matsumoto,
Hironao Kawashima and Tatsuru Daimon
VI Contents

Chapter 8 Lot Sizing and Scheduling in
Parallel Uniform Machines – A Case Study 151
F. Charrua Santos, Francisco Brojo and Pedro M. Vilarinho
Chapter 9 Use of Simulated Annealing Algorithms for Optimizing
Selection Schemes in Farm Animal Populations 179
Edo D’Agaro
Section 3 Hybrid SA Applications 199
Chapter 10 Simulated Annealing Evolution 201
Sergio Ledesma, Jose Ruiz and Guadalupe Garcia
Chapter 11 Design of Analog Integrated Circuits
Using Simulated Annealing/Quenching with
Crossovers and Particle Swarm Optimization 219
Tiago Oliveira Weber and Wilhelmus A. M. Van Noije
Chapter 12 Genetic Algorithm and Simulated Annealing:
A Combined Intelligent Optimization Method
and Its Application to Subsynchronous Damping
Control in Electrical Power Transmission Systems 245
Xiaorong Xie
Chapter 13 Fuzzy c-Means Clustering, Entropy Maximization,
and Deterministic and Simulated Annealing 271
Makoto Yasuda

Preface

Global optimization is computationally extremely challenging and, for large instances,
exact methods reach their limitations quickly. One of the most well-known
probabilistic meta-heuristics is Simulated Annealing (SA). Proposed initially to solve
discrete optimization problems, it was later extended to continuous domain. The
significant advantage of SA over other solution methods has made it a practical
solution method for solving complex optimization problems.
In this book, some advances in SA are presented. More specifically: criteria for the
number of evaluated solutions required to reach thermal equilibrium; crystallization
heuristics that add a feedback mechanism to the next candidate selection; and
estimation of the equilibrium quantities by the average quantity through the non-
equilibrium behavior. Subsequent chapters of this book will focus on the applications
of SA in signal processing, image processing, electric power systems, operational
planning, vehicle routing and farm animal mating. The final chapters combine SA
with other techniques to obtain the global optimum: artificial neural networks, genetic
algorithms and fuzzy logic.
This book provides the reader with the knowledge of SA and several SA applications.
We encourage readers to explore SA in their work, mainly because it is simple and
because it can yield very good results.
Marcos de Sales Guerra Tsuzuki

Department of Mechatronics and Mechanical Systems Engineering,
University of São Paulo,
Brazil

Section 1




Advances in SA