1f1f598314
The original tutorial link[http://paradiseo.gforge.inria.fr/index.php?n=Doc.Tutorials] is broken. I found the archive from here: https://web.archive.org/web/20210119160107/http://paradiseo.gforge.inria.fr/index.php?n=Doc.Tutorials
67 lines
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2.4 KiB
Markdown
67 lines
No EOL
2.4 KiB
Markdown
# How to use Tabu Search
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In this lesson, a simple tabu search is presented, using an order neighborhood based on a shift operator, to solve the Queen problem.
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1. Tabu Search on the Queen problem.
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2. Exercise
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## 1. Tabu Search (example on the Queen problem)
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First you have to define the representation of a Queen, how to initialize and how to evaluate it. So you have to declare three classes:
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```c++
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queenFullEval<Queen> fullEval;
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eoInitPermutation<Queen> init(vecSize);
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Queen sol1;
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```
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Then, you have to ramdomly intialize a solution:
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```c++
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init(sol1);
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fullEval(sol1);
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```
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Let see the most simple constructor of a Tabu Search (in mo/src/algo/moTS.h). You need five parameters:
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* a neighborhood
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```c++
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orderShiftNeighborhood orderShiftNH(pow(vecSize-1, 2));
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```
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* a full evaluation function (declared before)
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* a neighbor evaluation function*
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```c++
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moFullEvalByCopy<shiftNeighbor> shiftEval(fullEval);
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```
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* a time limit for the search (in seconds)
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* a size for the tabu list
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You can now declare the Tabu Search:
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```c++
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moTS<shiftNeighbor> localSearch1(orderShiftNH, fullEval, shiftEval, 2, 7);
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// 2 is the time limit, 7 is the size of the tabu List
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```
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This simple constructor uses by default seven components:
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* moTimeContinuator
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* moNeighborComparator
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* moSolNeighborComparator
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* moNeighborVectorTabuList
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* moDummyIntensification
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* moDummyDiversification
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* moBestImprAspiration
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More flexible constructors exist as you can change these components:
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```c++
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moNeighborVectorTabuList<shiftNeighbor> tl(sizeTabuList,0);
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moTS<shiftNeighbor> localSearch2(orderShiftNH, fullEval, shiftEval, 3, tl);
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// 3 is the time limit
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```
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In this one, the tabuList has been specified.
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```c++
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moTS<shiftNeighbor> localSearch3(orderShiftNH, fullEval, shiftEval,
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comparator, solComparator, continuator, tl, inten, div, asp);
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```
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In this one, comparators, continuator, tabu list, intensification strategy, diversification strategy and aspiration criteria have been specified.
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You can test these three algorithms by changing problem sizes, time limit and the size of tabu list (use parameters file or the option --vecSize=X, --timeLimit=Y and --sizeTabuList=Z on command line to execute "testSimpleTS"). It prints the initial and final solutions.
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## 2. Exercise
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1. Try to implement and use a diversification strategy in 'testSimpleTS". You can also use a predifined strategy: moMonOpDiversification (in "memory" directory) |