Guided Local Search is a metaheuristic search method. A meta-heuristic method is a method that sits on top of a local search algorithm to change its behaviour.
Tapas Kanungo et al provide C++ code (for Unix, under GPL) and documentation for k-means clustering based on a combination of local search and Lloyd's algorithm (also known as the k-means algorithm).
David J.C.
1 Local Search Algorithms and Optimization Problems . . . . . . . . . . . 120
4.2 Local Search in Continuous Spaces . . . . . . . . . . . . . . . . . . . . . 129
4.3 Searching with Nondeterministic Actions . . . . . . . . . . . . . . . . . . 133
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EAs global search ability can be used to locate a good region in the space and then a local search procedure can locate the near optimal point in that region.
" AAAI "Classic Paper" Award in 2008 for a seminal contribution to stochastic local search for constraint satisfaction and its broad influence on local search algorithms and applications in artificial intelligence.
Optimised Markov chain algorithms which utilise local searching heuristical sub-algorithms can find a route extremely close to the optimal route for 700-800 cities.
Local searches, such as hill climbing, simulated annealing and beam search, use techniques borrowed from optimization theory.[82] ...
 See also: Search algorithm, Branch, Genetic algorithm, Simulated annealing, Artificial intelligence
  
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