Timeline for Meaning of search methods and optimization methods
Current License: CC BY-SA 3.0
6 events
| when toggle format | what | by | license | comment | |
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| May 8, 2012 at 14:01 | vote | accept | Tim | ||
| May 4, 2012 at 14:48 | comment | added | Arnold Neumaier | A metaheuristic must contain principles more specific than just ''local search'' to deserve its naame; I never heard it apply this generally. But the terminology isn't very precise | |
| May 4, 2012 at 14:47 | comment | added | Arnold Neumaier | @Tim: A line search may or may not use gradients in its search (e.g., a Wolfe line search needs them). You shouldn't attach to these words a too precise meaning; they are suggestive of something, not mathematical concepts with a precise meaning. - Newton's method uses gradients and Hessians. - A method is stochastic once the search involves a random number generator. - local search may be used in a general sense of a method that doesn't guarantee convergence to a global optimum, or mean a direct search based on inspecting local neighborhoods of the current best point only. | |
| May 4, 2012 at 14:13 | comment | added | Tim | (3) Are search methods in its narrow sense all metaheuristic? | |
| May 4, 2012 at 14:13 | comment | added | Tim | Thanks! So for optimization problems, (1) In its broader sense, search is equialent to optimization methods. (2) In its narrower sense, does search "generally using function values only" mean "{search methods} = {optimization methods using function values only} $\cup$ {line search methods}" ? Is "line search" the only "search method" that uses things beyond function values? If I add some perturbation to gradient in a gradient based-method, does the method become a "stochastic search" method? Do local search and stochastic search both only use function values? | |
| May 4, 2012 at 11:49 | history | answered | Arnold Neumaier | CC BY-SA 3.0 |