Chapter 14. Selective Search
This chapter considers the design of algorithms to solve hard combinatorial optimization problems, where one in general is not able to guarantee the quality of the computed solutions. When evaluating the estimator to the last node of a path, local search algorithms can be adapted to the state space search, even if they do not systematically enumerate all possible paths.
Keywords: selective search, local search, hill-climbing, simulated annealing, tabu search, evolutionary search, randomized local search, genetic algorithm, approximate search, MAX-k-SAT, randomized search ant algorithm, simple ant system, vertex and walk, Lagrange multiplier, no-free-lunch
The heuristic search strategies considered so far were ...
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