I read about the hill climbing algorithms, the simulating annealing algorithm, but I am confused. What is the basic purpose of local search methods?
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Hill climbing, Simulated annealing, genetic algorithms are different variants of local search algorithm. Hill Climbing use to find good solution for NP-hard problems. Simulated annealing was first used extensively to solve VLSI layout problems. It has been applied widely to factory scheduling and other large-scale optimization tasks. Genetic algorithm have had a wide-spread impact on optimization problems, such as circuit layout and job-shop scheduling.
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2$\begingroup$ "Hill Climbing use to solve NP-hard problems"- please replace "solve" by "find good solutions for". Solving means in the sense how the NP-hard problem is phrased, e.g. guaranteed to find the optimal solution. $\endgroup$ – Martin Thoma Nov 26 '18 at 6:52
