* http://en.wikipedia.org/wiki/Heuristic_algorithm - Two fundamental goals in computer science are finding algorithms with provably good run times and with provably good or optimal solution quality. A heuristic is an algorithm that abandons one or both of these goals; for example, it usually finds pretty good solutions, but there is no proof the solutions could not get arbitrarily bad; or it usually runs reasonably quickly, but there is no argument that this will always be the case. ... Often, one can find specially crafted problem instances where the heuristic will in fact produce very bad results or run very slowly; however, such pathological instances might never occur in practice because of their special structure. ... There is a class of general heuristic strategies called metaheuristics, which often use randomized search for example. They can be applied to a wide range of problems, but good performance is never guaranteed.
* http://www.mathworks.com/matlabcentral/fileexchange/24838 - GODLIKE combines 4 global optimizers for both single/multi-objective optimizations ... genetic algorithm, differential evolution, particle swarm optimization and adaptive simulated annealing algorithms ... It is primarily intended to increase ROBUSTNESS, not efficiency