Memetic Algorithms and Complete Techniques
As mentioned in previous chapters in this volume, metaheuristics (and specifically MAs) have a part of their raison d’etre in practically solving problems whose resolution would be otherwise infeasible by means of other non-heuristic approaches. Such alternative non-heuristic approaches are complete methods that –unlike heuristics– do guarantee that the deviation from optimality of the solution they will provide is somehow bounded (and as a particular case, that the optimal solution will be found). These methods are eventually limited by the curse of dimensionality, yet they may still constitute a very interesting resource either from the application point of view, or from the lessons that can be learnt from them. Indeed, in some sense these approaches could be considered complementary to metaheuristics rather that mere “rivals”. Even more so in the case of MAs, whose philosophy has been since its inception much more flexible and integrative rather than dogmatic or exclusive.
KeywordsLocal Search Search Tree Hybrid Algorithm Memetic Algorithm Beam Search
Unable to display preview. Download preview PDF.