There are infinitely many ways of representing a d.c. function as a difference of convex functions. In this paper we analyze how the computational efficiency of a d.c.optimization algorithm depends on the representation we choose for the objective function, and we address the problem of characterizing and obtaining a computationally optimal representation. We introduce some theoretical concepts which are necessary for this analysis and report some numerical experiments. © 2008 Springer Science+Business Media, LLC.
|Journal||Journal of Global Optimization|
|Publication status||Published - 1 Apr 2009|
- Branch and bound
- Dc program
- Dc representation
- Outer approximation
- Semi-infinite program