Easy way to solve optimization problems

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The discussion centers on the challenge of formulating optimization problems in calculus rather than solving them. Participants suggest that the focus should be on modeling the problems, as many resources are available for learning this skill. A recommended link provides numerous examples and solutions for applied optimization. Additionally, the importance of understanding minimization in problems, such as linear regression, is highlighted. Overall, the conversation emphasizes the need for better problem formulation techniques in optimization.
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Hi, So i don't need help on any specific problem, I was just wondering if there was an easy way to solve optimization problems in calc. I have no problem doing most of it, its just that coming up with the functions is my biggest problem. Can anyone give me advice on coming up with the problems.
 
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sasuke07 said:
Hi, So i don't need help on any specific problem, I was just wondering if there was an easy way to solve optimization problems in calc. I have no problem doing most of it, its just that coming up with the functions is my biggest problem. Can anyone give me advice on coming up with the problems.

Your question is not clear, but you seem to be saying that you have more trouble coming up with the formulation of a problem than solving it; that is, your question is about modelling, not about solving. If that is the case, there are numerous books and articles dealing with optimization formulations. The following link seems particularly relevant; it contains numerous problems and solutions:
http://homepages.math.uic.edu/~dcabrera/practice_exams/topics/appliedoptimization.html
 
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Adding to Mr. Vickson's post (that is a cool website, by the way), many problems are set up as minimisations, that is wherever the function is at a minimum is your optimum solution. For example, in the case of fitting a line to a set of points (linear regression), you attempt to minimise the data misfit. The best resource I have for computing these minimisations is Nocedal and Wright: "Numerical Optimization." I think optimisation theory is a really cool field with tons of active research.
 
Question: A clock's minute hand has length 4 and its hour hand has length 3. What is the distance between the tips at the moment when it is increasing most rapidly?(Putnam Exam Question) Answer: Making assumption that both the hands moves at constant angular velocities, the answer is ## \sqrt{7} .## But don't you think this assumption is somewhat doubtful and wrong?

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