c1a44fd2a6
Add README.md files for moeo/tutorial/Lesson{1-4}, smp/tutorial/Lesson{1-4},
and mo/tutorial/Lesson9 — these tutorials had no documentation.
Fix return 1 → return 0 in 28 tutorial main() functions across mo/ and
smp/ that unconditionally returned failure status.
1.4 KiB
Variable Neighborhood Search (VNS)
VNS on the N-Queens problem, using multiple neighborhood structures to escape local optima.
The N-Queens problem places N queens on an N x N chessboard so that no two queens attack each other. The representation is a permutation (one queen per column) and the fitness counts conflicts (minimized).
Running
From the build/mo/tutorial/Lesson9 directory:
./VNS -V=12
This runs VNS on a 12-queens instance with a 3-second time limit.
How it works
VNS alternates between perturbation (shaking) and local search using different neighborhood structures. Here, two neighborhoods are used:
shiftNeighborhood shiftNH((vecSize-1) * (vecSize-1));
swapNeighborhood swapNH(vecSize * (vecSize-1) / 2);
Each has its own hill-climber and mutation operator:
moSimpleHC<shiftNeighbor> ls1(shiftNH, fullEval, shiftEval);
moSimpleHC<swapNeighbor> ls2(swapNH, fullEval, swapEval);
moRndVectorVNSelection<Queen> selectNH(ls1, shiftMut, true);
selectNH.add(ls2, swapMut);
moRndVectorVNSelection randomly picks which neighborhood/local search
to apply at each iteration. Forward (moForwardVectorVNSelection) and
backward (moBackwardVectorVNSelection) selection strategies are also
available. The search runs until the moTimeContinuator time limit:
moTimeContinuator<shiftNeighbor> cont(3); // 3 seconds
moVNS<shiftNeighbor> vns(selectNH, acceptCrit, fullEval, cont);