Answers.Body: <p>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.</p>
  
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2018-11-24T15:28:24.673Z
Answers.LastActivityDate: 2019-03-02T11:12:18.327Z
Answers.LastEditDate: 2019-03-02T11:12:18.327Z
Answers.UserDisplayName: Huma Qaseem
Body: <p>I read about the hill climbing algorithms, the simulating annealing algorithm, but I am confused. What is the basic purpose of local search methods?</p>
  
Tags: <optimization><search><hill-climbing><simulated-annealing><local-search>
Title: What is the basic purpose of local search methods?
UserDisplayName: Iram Shah
ThreadText: # What is the basic purpose of local search methods?
  
  (Asked by: username_0 on 2018-11-19)
  
  I read about the hill climbing algorithms, the simulating annealing algorithm, but I am confused. What is the basic purpose of local search methods?
  
  **Tags:** optimization, search, hill-climbing, simulated-annealing, local-search
  
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  ## 1 answers
  
  ### Answer by username_1 on 2018-11-24. Score: 0 | Accepted answer
  
  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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