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Answer :
Final answer:
The multi-start feature of solver in computational optimization deals with the problem of local optima. By starting from different points, it increases the chance of finding the most optimal (global optimum) solution.
Explanation:
The multi-start feature of solver is a technique used in mathematics, specifically in computational optimization where multiple problems need to be solved. The multi-start feature is used to address the issues presented by local optima. Local optima in an optimization problem are the points that give the best output or solution in their local neighborhood, but they may not provide the best solution for the entire problem. Therefore, by starting the solver from various points, a more global optimum can potentially be found. For example, if you're trying to find the lowest point in a range of hills and valleys (a typical optimization problem), each hill's bottom could be a local optimum, but there's only one lowest point for the entire range which is the global optimum. The multi-start feature would explore multiple hills (start points), increasing the likelihood of finding that lowest, global optimum point.
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Answer:
The multi-start feature of solver solves the problem multiple times, each with a different starting point in the attempt to address the problems presented by local optima.
