Iterated Greedy

The iterated greedy algorithm generates a sequence of solutions by iterating over a constructive heuristic using destruction and construction phases. In the last few years, it has been employed to solve a considerable number of optimization problems, including some diversity and dispersion problems. The first part of this chapter is devoted to the revision of the basic components for the design of this metaheuristic. It also presents the changes and extensions to the original iterated greedy methodology that have been recently explored to provide advanced implementations being able to achieve high-quality solutions to difficult optimization problems. With the aim of providing additional results and insights on the application of iterated greedy to face diversity and dispersion problems, the second part of the chapter is dedicated to contribute with a perturbation-based iterated greedy for the large-scale MaxMin diversity problem (an extremely complex optimization problem, since it joins high dimensionality with a max-min objective function). Extensive experiments verify that the proposal can achieve better solution quality than the state-of-the-art optimizer for this diversity maximization problem and other competing algorithms.