This document discusses the meta-heuristic technique of Tabu Search (TS). It begins with an outline that covers the motivation for TS, background information, main concepts, algorithms, examples, and applications. TS was proposed by Glover in 1986 as a local search algorithm that uses memory to avoid getting stuck in local optima. The key feature of TS is the use of memory, in the form of a tabu list, to record previously visited solutions and avoid cycling. The tabu list is updated each iteration on a first-in, first-out basis. TS guides the search towards unexplored regions of the solution space, even if it means accepting non-improving moves, in order to escape local optima. Example
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Tabu search
1. Scientific Research Group in Egypt (SRGE)
Meta-heuristics techniques (I)
Tabu search
Dr. Ahmed Fouad Ali
Suez Canal University,
Dept. of Computer Science, Faculty of Computers and informatics
Member of the Scientific Research Group in Egypt
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Tabu search (TS)(Background)
• Tabu search (TS) algorithm was proposed
by Glover (1986).
•In the 1990s, the tabu search algorithm
became very popular in solving
optimization problems.
•Nowadays, it is one of the most wide
spread (single ) S-metaheuristics.
•The use of memory represents the
particular feature of tabu search.
•TS behaves like a steepest LS algorithm, but it
accepts nonimproving solutions to escape from
local optima.
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Tabu search (main concepts)
• The key feature of TS method is the use
of memory, which records information
related of the search process.
•TS generates a neighborhood solution
from the current solution and accepts the
best solution even if is not improving the
current solution.
This strategy may lead to cycles
i.e the previous visited solutions could
be selected again.
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Tabu search (main concepts)
• In order to avoid cycles, TS discards the
solution that have been previously visited
by using memory which is called tabu list.
•The length of the memory (tabu list)
control the search process.
•A high length of the tabu list is high the
search will explore larger regions and
forbids revisiting high number of solution.
•A low length of the tabu list concentrates
the search on a small area of the search
space.
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Tabu search (main concepts)
• At each iteration the tabu list is
updated (first in – first out queue).
•The tabu list contains a constant
number of tabu moves called tabu
tenure, which is the length of time for
which a move is forbidden.
•If a move is good and can improve the
search process but it is in tabu list, there
is no need to be prohibited and the
solution is accepted in a process called
aspiration criteria.
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References
Metaheuristics From design to implementation, El-Ghazali
Talbi, University of Lille – CNRS – INRIA.
F. Glover, Future paths for integer programming and links to
artificial intelligence, Computers and Operations Research 13
(1986), 533-549.