Evolutionary algorithms (EA) are a family of analytical approaches loosely based on a selection-of-the-fittest evolutionary metaphor. Variants of EA are commonly applied to semistructured and multiobjective problems because they are not constrained by the same underlying assumptions on which many more traditional approaches are built. These kinds of problems are common in geographical analysis, and their solution often presents a challenge because (a) not all objectives can be formulated in mathematical terms and (b) the set of all possible solutions (i.e., the solution space) that must be analyzed can increase rapidly as a function of problem size, thus rendering real-world problem solving intractable. Innovative methods are, therefore, needed that trim the number of analyzed solutions to a manageable number (i.e., a heuristic must be used). ...