I was wondering if anybody had any suggestions for texts or survey articles on decomposition methods (e.g. primal, dual, Dantzig–Wolfe decompositions) for solving large mathematical programming problems.

I liked Stephen Boyd's "Notes on Decomposition Methods", and it would be great to find for example a textbook that covers this topic in more detail.


Lately I've been working with Decomposition Techniques in Mathematical Programming: Engineering and Science Applications by Conejo, Castillo, Minguez and Garcia-Bertrand (http://www.springer.com/engineering/computational+intelligence+and+complexity/book/978-3-540-27685-2).

It covers several different techniques and when they are applicable, including Dantzig-Wolfe and Benders, and I find it has a good balance of theory and application. I particularly like the examples, because I think they closely resemble real problems I might wish to formulate and solve.


By method that Constraint matrix convert to vector, Nowadays, decomposition methods is often not using for solving large optimization problems.

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    $\begingroup$ What do you mean by "By method that Constraint matrix convert to vector" ? $\endgroup$ – Amelio Vazquez-Reina Jun 21 '13 at 13:02

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