Parallel and Distributed Hybrid Optimization Models for Grids
Abstract
This paper deals with hybrid optimization schemes that combine meta-heuristics and exact optimization methods. In particular, Genetic Algorithms (GAs) and the Branch-and-Bound algorithm (B&B). Three parallel hybridization schemes combining GAs and the B&B algorithm are proposed: a parallel relay model where the two algorithms are executed in a pipeline mode, a low level hybrid scheme where a given operator of the GA is replaced by a B&B solver, and a cooperative hybrid scheme where the two algorithms cooperate and exchange information about: best-found solution, promising regions to exploit by the B&B and unexplored regions to explore by the GA.