Overview: Meta-heuristics have developed dramatically since theirinception in the early 1980s. They have had widespread success inattacking a variety of practical and difficult combinatorialoptimization problems. These families of approaches include, but arenot limited to greedy random adaptive search procedures, geneticalgorithms, problem-space search, neural networks, simulatedannealing, tabu search, threshold algorithms, and their hybrids. Theyincorporate concepts based on biological evolution, intelligentproblem solving, mathematical and physical sciences, nervous systems,and statistical m
|