Simulated Annealing (SA) is probabilistic and an optimization technique, and it helps to find out the global optimum for a given function.
The local beam search algorithm begins with randomly generated states and keeps track of them to find out the best until it achieves a goal.
A genetic algorithm selects two parents based on their fitness, crossover those parents to produce offspring, and randomly mutates each offspring.
Hill-climbing search algorithm terminates when it reaches a peak where no neighbor has a higher value.
Types of Local Search Algorithms
About the Author: Gopi Chandrakesan
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