Well yes, that is what the max and min stand for, but there is definitely more to it in analysis. Both the max/min notation and the triangle inequality allow you to make estimates. If you have the inequality |x-a| < min(epsilon, 1), then the most important thing this inequality is telling you is that |x-a| < epsilon AND |x-a| < 1 (Why?). The most basic application of this used to prove limits of quadratic equations, where sometimes it is convenient to make the simplifying assumption that [itex]\delta \leq 1[/itex] so that |x-a| < 1 (if x is approaching a). Then this assumption will typically allow you to find a bound on |x-a| in terms of epsilon. Then to justify the use of the assumption that [itex]\delta \leq 1[/itex], we use the min notation |x-a| < min((some positive factor)*epsilon, 1). Similarly, the max notation is often useful when we're dealing with limits approaching infinity.
The triangle inequality really depends on the fact that you can add and subtract the same number to some other quantity for free since it's the same as adding 0. Ideally, you'll already have made some decent estimates in your problem, and you just need to tie them together (this is completely analogous to the situation where you needed max/min). For instance, if you found that |f(x) - L| < epsilon and |g(x) - L| < epsilon, and you wanted to find an estimate on |f(x) - g(x)|, then note that you can introduce L in the last expression by noting that
[tex]|f(x) - g(x)| = |f(x) -L + L - g(x)| \leq |f(x) -L| + |L - g(x)| = |f(x) -L| + |g(x) - L| < \varepsilon + \varepsilon.[/tex]
Application of the triangle inequality is very intuitive, since all we're saying is that if f is close to L, and g is close to L, then f and g should be near each other as well. For further reading, I suggest trying to find a copy of Spivak's Calculus text and reading chapter 5 (google books might have it), or some other intro analysis text.