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I understand the basic operation of the algorithms however i'm unclear as to when to use one over the other and what advantages/disadvantages they offer over each other.

Also as an aside, if anyone knows any good resources that go over the topic of optimization in detail (especially gradient free optimization) that I could read or watch, i'd really appreciate it if you could point me in the right direction.

Thanks in advance guys and apologies if its a basic question, I'm quite new to the topic.

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  • $\begingroup$ I would say that problems for which you can reliably use the derivative tend to be easier. So always use that if you can and only go with derivative-free methods if you must. $\endgroup$ – Juho Aug 8 '19 at 17:36
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Actually, derivative methods such as random search shorten the time allocated for function evaluation if the problem is big. On the other hand, derivative-free methods take much time to complete function evaluation that leads to a dramatic increase in optimization time.

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