I. Introduction
The complexity of real-world engineering optimization problems gives rise to various kinds of metaheuristics that use stochastic techniques to effectively explore the search space for a global optimum. Many of their names, such as genetic algorithms [1] and simulated annealing [2], attest to the influence of natural or biological analogies, and ingeniously harnessing such analogies often leads to very effective computer algorithms [3].