Metaheuristics for optimization problems in computer communications

Recent years have witnessed huge advances in computer technology and communication networks, entailing hard optimization problems in areas such as network design and routing. Metaheuristics are general high-level procedures that coordinate simple heuristics and rules to find good approximate solutions to computationally difficult combinatorial optimization problems. They are among the most effective solution strategies for solving optimization problems in practice and have been applied to a very large variety of problems in telecommunications, computer communications, and network design and routing. In this paper, we review the principles associated with some of the main metaheuristics and we give templates for basic implementations of them: simulated annealing, tabu search, GRASP, VNS, genetic algorithms, and path-relinking. The main strategies underlying the development of parallel implementations of metaheuristics are also reviewed. Finally, we present an account of some successful applications of metaheuristics to optimization problems in telecommunications, computer communications, and network design and routing.