The correct answer is: D. Less memory & Finds a solution in large infinite space
Local search algorithms are a type of heuristic algorithm that iteratively improves a solution by making small changes to it. They are not guaranteed to find the optimal solution, but they can be very effective in finding good solutions to problems with large search spaces.
One of the key advantages of local search algorithms is that they require less memory than other types of algorithms. This is because they only need to store the current solution and the best solution found so far. Other types of algorithms, such as branch and bound, need to store all of the possible solutions that have been explored. This can be a significant advantage for problems with large search spaces.
Another advantage of local search algorithms is that they can often find solutions to problems with large infinite spaces. This is because they do not need to explore all of the possible solutions. Instead, they can start with a random solution and then iteratively improve it until it reaches a local optimum.
However, local search algorithms also have some disadvantages. One disadvantage is that they are not guaranteed to find the optimal solution. Another disadvantage is that they can be slow to converge to a solution, especially for problems with large search spaces.
Overall, local search algorithms are a powerful tool for solving problems with large search spaces. They are not guaranteed to find the optimal solution, but they can often find good solutions quickly and with less memory than other types of algorithms.
Here is a brief explanation of each option:
- Option A: Less memory. Local search algorithms require less memory than other types of algorithms because they only need to store the current solution and the best solution found so far. Other types of algorithms, such as branch and bound, need to store all of the possible solutions that have been explored. This can be a significant advantage for problems with large search spaces.
- Option B: More time. Local search algorithms can be slow to converge to a solution, especially for problems with large search spaces. This is because they do not guarantee to find the optimal solution, and they can get stuck in local optima.
- Option C: Finds a solution in large infinite space. Local search algorithms can often find solutions to problems with large infinite spaces. This is because they do not need to explore all of the possible solutions. Instead, they can start with a random solution and then iteratively improve it until it reaches a local optimum.
- Option D: Less memory & Finds a solution in large infinite space. This is the correct answer. Local search algorithms require less memory than other types of algorithms and can often find solutions to problems with large infinite spaces.