Meta-Heuristics: Theory and Applications

675 Pages·1996·22.07 MB·English

by  Ibrahim H. Osman

lVIETA-HEURISTICS:
Theory and Applications
META-HEURISTICS:
Theory & Applications
edited by
Ibrahim H. Osman
and
James P. Kelly
"~.
Kluwer Academic Publishers
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Library of Congress Cataloging-in-Publication Data
A C.I.P. Catalogue record for this book is available from the Library of
Congress.
ISBN-13: 978-1-4612-8587-8 e-ISBN-13: 978-1-4613-1361-8
DOT: 10.1007/978-1-4613-1361-8
Copyright © 1996 by Kluwer Academic Publishers
Softcover reprint of the hardcover 1s t edition 1996
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Table of Contents
Ch. 1 Ibrahim H. Osman and James P. Kelly "Meta-Heuristics: An
Overview" . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. 1
GENETIC ALGORITHMS
Ch. 2 David Levine "A Parallel Genetic Algorithm for the Set
Partitioning Problem" ................................ 23
Ch.3 Zbigniew Michalewicz "Evolutionary Computation and Heuristics" 37
Ch.4 Heinz Miihlenbein and Hans-Michael Voigt "Gene Pool
Recombination in Genetic Algorithms" ..................... 53
Ch.5 Mutsunori Yagiura and Toshihide Ibaraki "Genetic and Local
Search Algorithms as Robust and Simple Optimization Tools" ..... 63
NETWORKS AND GRAPHS
Ch. 6 Geoff Craig, Mohan Krishnamoorthy and M. Palaniswami
"Comparison of Heuristic Algorithms for the Degree Constrained
Minimum Spanning Tree" .............................. 83
Ch. 7 Rafael Marti "An Aggressive Search Procedure for the Bipartite
Drawing Problem" ................................... 97
Ch.8 Yazid M. Sharaiha and Richard Thaiss "Guided Search for the
Shortest Path on Transportation Networks" .................. 115
SCHEDULING AND CONTROL
Ch. 9 H. Abada and E. EI-Darzi "A Metaheuristic for the Timetabling
Problem" ......................................... 133
Ch.l0 Peter Brucker and Johann Hurink "Complex Sequencing
Problems and Local Search Heuristics" .................... 151
vi
Ch. 11 Mauro Dell' Amico, Silvano Martello and Daniele Vigo "Heuristic
Algorithms for Single Processor Scheduling with Earliness and Flow
Time Penalties" ..................................... 167
Ch. 12 Gregor P. Henze, Manuel Laguna and Moncef Krarti "Heuristics
for the Optimal Control of Thermal Energy Storage" ........... 183
Ch.13 Helmut E. Mausser and Stephen R. Lawrence "Exploiting Block
Structure to Improve Resource-Constrained Project Schedules" .... 203
Ch.14 Helena Ramalhinho Lourenc;o and Michiel Zwijnenburg
"Combining the Large-Step Optimization with Tabu-Search:
Application to The Job-Shop Scheduling Problem" ............. 219
Ch. 15 Takeshi Yamada and Ryohei Nakano "Job-Shop Scheduling by
Simulated Annealing Combined with Deterministic Local Search" .. 237
SIMULATED ANNEALING
Ch.16 Mark A. Fleischer & Sheldon H. Jacobson "Cybernetic
Optimization by Simulated Annealing: An Implementation of
Parallel Processing Using Probabilistic Feedback Control" ...... 249
Ch.17 Jean-Luc Lutton and Emmanuelle Philippart "A Simulated
Annealing Algorithm for the Computation of Marginal Costs of
Telecommunication Links" ............................. 265
Ch. 18 Norman M. Sadeh and Sam R. Thangiah "Learning to Recognize
(Un) Promising Simulated Annealing Runs: Efficient Search
Procedures for Job Shop Scheduling and Vehicle Routing" ....... 277
Ch. 19 Mike B. Wright and Richard C. Marett "A Preliminary
Investigation into the Performance of Heuristic Search Methods
Applied to Compound Combinatorial Problems" .............. 299
TABU SEARCH
Ch. 20 Ahmed S. AI-Mahmeed "Tabu Search, Combination and
Integration" ........................................3 19
vii
Ch.21 Roberto Battiti, Giampietro Tecchiolli and Paolo Tonella "Vector
Quantization with the Reactive Tabu Search" ............... 331
Ch. 22 Diane Castelino and Nelson Stephens "Tabu Thresholding for the
Frequency Assignment Problem" ........................ 343
Ch. 23 Mauro Dell' Amico and Francesco MamoU "A New Tabu Search
Approach to the 0-1 Equicut Problem" .................... 361
Ch.24 Kathryn A. Dowsland "Simple Tabu Thresholding and the Pallet
Loading Problem" .................................. 379
Ch.25 Fred Glover and Gary A. Kochenberger "Critical Event Tabu
Search for Multidimensional Knapsack Problems" . . . . . . . . . . .. 407
Ch.26 Fred Glover, John M. Mulvey and Kjetil Hoyland "Solving
Dynamic Stochastic Control Problems in Finance Using Tabu
Search with Variable Scaling" .......................... 429
Ch.27 S. Hanafi, A. Freville and A. EI Abdellaoui "Comparison of
Heuristics for the 0-1 Multidimensional Knapsack Problem" ..... 449
Ch.28 Arne Lfjkketangen and Fred Glover "Probabilistic Move Selection
in Tabu Search for Zero-One Mixed Integer Programming
Problems" . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 467
Ch. 29 Lutz Sondergeld and Stefan Vo8 "A Star-Shaped Diversification
Approach in Tabu Search" ............................ 489
Ch. 30 Michel Toulouse, Teodor G. Crainic and Michel Gendreau
"Communication Issues in Designing Cooperative Multi-Thread
Parallel Searches" . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 503
Ch.31 Fan T. Tseng "A Study on Algorithms for Selecting r Best
Elements from An Array" .......................... ... 523
Ch. 32 Vicente Valls, M. Angeles Perez, M. Sacramento Quintanilla "A
Modified Tabu Thresholding Approach for the Generalised
Restricted Vertex Colouring Problem" .................... 537
viii
Ch.33 David L. Woodruff "Chunking Applied to Reactive Tabu Search" 555
Ch.34 Martin Zachariasen and Martin Dam "Tabu Search on the
Geometric Traveling Salesman Problem" .................. 571
TRAVELING SALESMAN PROBLEMS
Ch. 35 Irene Charon and Olivier Hudry "Mixing Different Components of
Metaheuristics" .................................... 589
Ch.36 H.M.M. ten Eikelder, M.G.A. Verhoeven, T.W.M. Vossen and
E.H.L. Aarts "A Probabilistic Analysis of Local Search" ....... 605
Ch. 37 Jean-Yves Potvin and Fran~ois Guertin "The Clustered Traveling
Salesman Problem: A Genetic Approach" .................. 619
VEHICLE ROUTING PROBLEMS
Ch.38 Richard W. Eglese and Leon Y. O. Li "A Tabu Search Based
Heuristic for Arc Routing with a Capacity Constraint and
Time Deadline" .................................... 633
Ch. 39 Hassan Ghaziri "Supervision in the Self-Organizing Feature Map:
Application to the Vehicle Routing Problem" ................ 651
Ch.40 Cesar Rego and Catherine Roucairol "A Parallel Tabu Search
Algorithm Using Ejection Chains for the Vehicle Routing
Problem" ........................................ 661
Ch. 41 Paolo Toth and Daniele Vigo "Fast Local Search Algorithms for
the Handicapped Persons Transportation Problem" ........... 677
Preface
The objective of this volume is to consolidate works in Operations Research,
Management Science, Artificial Intelligence, Computer Science, and related fields to
further the understanding of basic principles and new developments in
Metaheuristics, including Genetic Algorithms, Neural Networks, Simulated
Annealing, Tabu Search, and other approaches for solving hard combinatorial
optimization. The included papers are a reviewed subset of the papers presented at
the 1995 Meta-Heuristics International Conference (MIC) held in Breckenridge,
Colorado, USA, 22-26 July 1995.
MIC-95 Committee:
Fred Glover James P. Kelly Ibrahim H. Osman
General Chair Organizing Chair Programme Chair
University of Colorado University of Colorado University of Kent
Boulder, Colorado Boulder, Colorado Cantebury Kent, UK
The International Scientific Program Committee members are:
Alain Hertz, Switzerland Heinz Muhlenbein, Germany
Bennet Fox, USA Jan Karel Lenstra, Netherlands
Bruce L. Golden, USA Jun Wang, USA
Catherine Roucairol, France Luk N. Van Wassenhove, France
Celso R. Ribeiro, Brazil Martine Labbe, Belgium
Chris Potts, UK Paolo Toth, Italy
Colin Reeves, UK Rainer Burkard, Austria
Darrell Whitley, USA Ramesh Sharda, USA
David Johnson, USA Richard Eglese, UK
Dominique de Werra, Switzerland Silvano Martello, Italy
Erwin Pesch, Germany Stefan VoB, Germany
Emile Aarts, Netherlands Teodor G. Crainic, Canada
Francesco Maffiolli, Italy Toshihide Ibaraki, Japan
Gilbert Laporte, Canada Zbigniew Michalewicz, USA
Harvey Greenberg, USA
x
We would like to thank all the referees:
E. H.L. Aarts J. Hurink C. Rego
D. Abramson T.Ibaraki C. C. Ribeiro
R. Alvares L. Ingber E. Rolland
R. Battiti D. S. Johnson C. Roucairol
A Van Breedam M. Krishnamoorthy R. A Russell
P. Brucker M. Labbe F. Semet
J. Chakrapani M. Laguna Y. M. Sharaiha
L Charon G. Laporte R. Sharda
A Colorni J. K. Lenstra J. Skorin-Kapov
D. Costa D. Levine P. Soriano
T. Crainic A Lokketangen E. Taillard
M. Dell'Amico H. Ramalhinho Louren~o G. Tecchiolli
P. Djang L.Lu S. R. Thangiah
M. Dorigo J.-L. Lutton B. Thiesse
U. Dorndorf F. Maffioli P. Toth
K. A Dowsland V. Maniezzo M. Toulouse
R. W. Eglese S. Martello M. Trubian
E. EI-Darzi H. Mausser V. Valls
E. Faulkenauer Z. Michalewicz M. G. A Verhoeven
C. Fleurent H. Miihlenbein D. Vigo
B. Fox W. Nujiten S. Voil
F. Glover L H. Osman J. Wang
B. L. Golden M. Otto D. Whitley
P. Greistorfer E. Pesch D. Woodruff
F. Guertin M. Pirlot M. Wright
A Hertz C. N. Potts J.Xu
G. Hoscheit J.-Y. Potvin T. Yamada
J. Huh C. R. Reeves S. Zenios
We would like to thank the College of Business at the University of Colorado and, the
Institute of Mathematics and Statistics at Kent University, United Kingdom, for
providing staff and financial support. We also would like to thank Gary Folven and
Carolyn Ford of Kluwer Academic Publishers for their editorial assistance in
producing this volume. Finally, we especially wish to thank Winnie Bartley and
Dolores Randall of the University of Colorado for their invaluable assistance in
producing this book.
Editors: LH. Osman and J.P. Kelly
1
Meta-Heuristics: An Overview
Ibrahim H. Osman
Institute of Mathematics and Statistics
University of Kent, Canterbury
Kent CT2 7NF, U.K
E-mail: [email protected]
&
James P. Kelly
School of Business
Campus Box 419
University of Colorado
Boulder, CO 80309, USA
E-mail: Ja [email protected]
Abstract:
Meta-heuristics are the most recent development in approximate search
methods for solving complex optimization problems, that arise in busi
ness, commerce, engineering, industry, and many other areas. A
meta-heuristic guides a subordinate heuristic using concepts derived from
artificial intelligence, biological, mathematical, natural and physical
sciences to improve their performance. We shall present brief overviews
for the most successful meta-heuristics. The paper concludes with future
directions in this growing area of research.
Keywords: Adaptive search, Approximate algorithms, Combinatorial
optimization, Genetic algorithms, Heuristics, Hybrids, Neural networks,
Simulated annealing, Tabu search.
1 Introduction
Meta-heuristics have developed dramatically since their inception in the
early 1980s. They have had widespread success in attacking a variety of
practical and difficult combinatorial optimization problems. These
families of approaches include but are not limited to greedy random
adaptive search procedure, genetic algorithms, problem-space search,
neural networks, simulated annealing, tabu search, threshold algorithms,
and their hybrids. They incorporate concepts based on biological evol
ution, intelligent problem solving, mathematical and physical sciences,