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<H1>Tabu Search</H1></CENTER>
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<H2>Overview</H2></FONT>The basic concept of Tabu Search as described by Glover 
(1986) is "a meta-heuristic superimposed on another heuristic. The overall 
approach is to avoid entrainment in cycles by forbidding or penalizing moves 
which take the solution, in the next iteration, to points in the solution space 
previously visited ( hence "tabu"). The Tabu search is fairly new, Glover 
attributes it's origin to about 1977 (see Glover, 1977). The method is still 
actively researched, and is continuing to evolve and improve. The Tabu method 
was partly motivated by the observation that human behavior appears to operate 
with a random element that leads to inconsistent behavior given similar 
circumstances. As Glover points out, the resulting tendency to deviate from a 
charted course, might be regretted as a source of error but can also prove to be 
source of gain. The Tabu method operates in this way with the exception that new 
courses are not chosen randomly. Instead the Tabu search proceeds according to 
the supposition that there is no point in accepting a new (poor) solution unless 
it is to avoid a path already investigated. This insures new regions of a 
problems solution space will be investigated in with the goal of avoiding local 
minima and ultimately finding the desired solution. 
<P>The Tabu search begins by marching to a local minima. To avoid retracing the 
steps used, the method records recent moves in one or more Tabu lists. The 
original intent of the list was not to prevent a previous move from being 
repeated, but rather to insure it was not reversed. The Tabu lists are 
historical in nature and form the Tabu search memory. The role of the memory can 
change as the algorithm proceeds. At initialization the goal is make a coarse 
examination of the solution space, known as 'diversification', but as candidate 
locations are identified the search is more focused to produce local optimal 
solutions in a process of 'intensification'. In many cases the differences 
between the various implementations of the Tabu method have to do with the size, 
variability, and adaptability of the Tabu memory to a particular problem domain. 
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<H2>Application Domain</H2></FONT>The Tabu search has traditionally been used on 
combinatorial optimization problems. The technique is straightforwardly applied 
to continuous functions by choosing a discrete encoding of the problem. Many of 
the applications in the literature involve integer programming problems, 
scheduling, routing, traveling salesman and related problems. <FONT 
color=#111aa0>
<H2>Software</H2></FONT><A title="Reactive Tabu Search" 
href="http://www.cacr.caltech.edu/~battiti/archive/code/rts_qap/README.html"><EM>Reactive 
Tabu Search</EM></A> R. Battiti, C source for Reactive Tabu Search 
<P><A href="http://www.cs.sandia.gov/opt/survey/demos.html"><FONT 
size=+1>Demo</FONT></A> <FONT color=#111aa0>
<H2>References</H2></FONT>R. Battiti, "Reactive search: Toward self-tuning 
heuristics", In V. J. Rayward-Smith, editor, <EM>Modern Heuristic Search 
Methods</EM>, chapter 4, pages 61--83. John Wiley and Sons Ltd, 1996. <BR><BR>R. 
Battiti and G. Tecchiolli, "Simulated annealing and tabu search in the long run: 
a comparison on qap tasks", <EM>Computer Math. Applic.</EM>, 28(6):1--8, 1994. 
<BR><BR>A M. Dell'Amico , A M. Trubian, "Applying Tabu Search to the Job-shop 
Scheduling Problem", <EM>J Annals of Ops. Res.</EM>, 41, 1993 <BR><BR>Glover 
F.," Future paths for Integer Programming and Links to Artificial Intelligence", 
<EM>Computers and Operations Research</EM>, 5:533-549, 1986. <BR><BR>Glover F., 
"Tabu Search: A Tutorial", <EM>Interfaces</EM>, 20(4):74-94,1990. 
<BR><BR>Glover, F. and D. de Werra,<A title="Tabu Search" 
href="http://www.baltzer.nl/anor/anor41.html"><EM>Tabu Search</EM></A>, Baltzer 
Science Publishers, 199 <BR><BR>Glover F., and Laguna M., Tabu Search, in 
<EM>Modern Heuristic Techniques for Combinatorial Problems</EM>, C.R. Reeves, 
editor, John Wiley &amp; Sons, Inc, 1993 <BR><BR>A Hertz, "Finding a Feasible 
Course Schedule Using Tabu Search", <EM>Discrete Applied Mathematics and 
Combinatorial Operations Research and Computer Science</EM>, 35, 1992 <BR><BR>A 
M. Laguna, A J. W. Barnes, A F. Glover, "Tabu Search Methodology for a Single 
Machine Scheduling Problem", <EM>J. of Int. Manufacturing</EM>, 2, 63-74, 1991 
<BR><BR>A M. Laguna, A J. L. Gonzalez-Velarde, "A Search Heuristic for 
Just-in-time Scheduling in Parallel Machines", <EM>J. of Int. Manu.</EM>, 2, 
253-260, 1991 <BR><BR>A S. C. S. Porto, A C.C. Ribeiro , "Parallel Tabu Search 
Message-Passing Synchronous Strategies for Task Scheduling under Precedence 
Constraints", <EM>Journal of Heuristics</EM>, V 1, 1995 <BR><BR>A S. C. S. 
Porto, A C.C. Ribeiro, "A Tabu Search Approach to Task Scheduling on 
Heterogeneous Processors under Precedence Constraints", <EM>International 
Journal of High-Speed Computing</EM>, 7(2), 1995 <BR><BR>A M. Widmer, "The 
Job-shop Scheduling with Tooling Constraints: A Tabu Search Approach", <EM>J. 
Opt. Res. S</EM>, 42, 75-82, 1991 <BR><BR>A M. Widmer, A A. Hertz, "A New 
Heuristic Method for the Flow Shop Sequencing Problem", <EM>Euro. J. Opt. 
Res.</EM>, 41, 186-193, 1989 <BR><BR><FONT color=#111aa0>
<H2>Miscellaneous Links</H2></FONT><A title="Reactive Tabu Search" 
href="http://www.cacr.caltech.edu/~battiti/reactive.html"><EM>Reactive Tabu 
Search</EM></A> R. Battiti, Reactive Tabu Search papers 
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<ADDRESS><A href="http://www.cs.sandia.gov/opt/survey/main.html">Global 
Optimization Survey - Main Page</A><BR><A href="http://www.sandia.gov/">Sandia 
National Laboratories</A><BR><BR>This page maintained by <A 
href="mailto:wehart@cs.sandia.gov">wehart@cs.sandia.gov</A> </ADDRESS>Last 
modified: March 10, 1997 </BODY></HTML>

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