I've been getting myself involved with this topic and would like to read more to gain a conceptual understanding of the various techniques and what each one is trying to achieve and their 'idea' behind achieving it. Basically the 'big-picture' view of things excluding the complicated math if possible.I've read numerous articles on the web and TCS too :) but still would like to know some good references for the layman (i.e. if you were to explain the various concepts/ideas to your wife/mother/child what you recommend them?) I know they wouldn't all be listed in one book but even if they are spread out across books that's fine.I'm quite interested in learning about nonlinear programming, semi-definite programming, convex optimization, I'm fairly well versed with linear/integer programming and do have a decent background in algorithms and a strong CS background too :)I may not have a strong mathematical background as probably required by these topics and before I develop it I'd like to have some 'fun' understanding the 'what, why and how' at a more humane level before diving into the math :)What would be some good references for the above? Good books/links covering other aspects of optimization but not listed above would be welcome to.
What are some good references for mathematical optimization for the layman?
reference request;soft question;optimization;big list;big picture
This is a very vast topic. For nonlinear optimization the book by Bertsekas is a standard reference. For convex optimization you should look at Boyd and Vandenberghe. For linear programming, the book by Schrijver is a reasonable (but dense) source. But you should also look at course material. Each of the authors mentioned above also has course material/lecture slides that might be useful. 