Grouping genetic operators for the delineation of functional areas based on spatial interaction

The delineation of functional economic areas, or market areas, is a problem of high practical relevance, since the delineation of functional sets such as economic areas in the US, Travel-to-Work Areas in the United Kingdom, and their counterparts in other OECD countries are the basis of many statistical operations and policy making decisions at local level. This is a combinatorial optimisation problem defined as the partition of a given set of indivisible spatial units (covering a territory) into regions characterised by being (a) self-contained and (b) cohesive, in terms of spatial interaction data (flows, relationships). Usually, each region must reach a minimum size and self-containment level, and must be continuous. Although these optimisation problems have been typically solved through greedy methods, a recent strand of the literature in this field has been concerned with the use of evolutionary algorithms with ad hoc operators. Although these algorithms have proved to be successful in improving the results of some of the more widely applied official procedures, they are so time consuming that cannot be applied directly to solve real-world problems. In this paper we propose a new set of group-based mutation operators, featuring general operations over disjoint groups, tailored to ensure that all the constraints are respected during the operation to improve efficiency. A comparative analysis of our results with those from previous approaches shows that the proposed algorithm systematically improves them in terms of both quality and processing time, something of crucial relevance since it allows dealing with most large, real-world problems in reasonable time.

Molecules, wing pattern and distribution: an approach to species delimitation in the "loxurina group" (Lepidoptera: Lycaenidae: Penaincisalia)

The wide range of morphological variations in the “loxurina group” makes taxa identification difficult, and despite several reviews, serious taxonomical confusion remains. We make use of DNA data in conjunction with morphological appearance and available information on species distribution to delimit the boundaries of the “loxurina” group species previously established based on morphology. A fragment of 635 base pairs within the mtDNA gene cytochrome oxidase I (COI) was analysed for seven species of the “loxurina group”. Phylogenetic relationships among the included taxa were inferred using maximum parsimony and maximum likelihood methods. Penaincisalia sigsiga (Bálint et al), P. cillutincarae (Draudt), P. atymna (Hewitson) and P. loxurina (C. Felder & R. Felder) were easily delimited as the morphological, geographic and molecular data were congruent. Penaincisalia ludovica (Bálint & Wojtusiak) and P. loxurina astillero (Johnson) represent the same entity and constitute a sub-species of P. loxurina. However, incongruence among morphological, genetic, and geographic data is shown in P. chachapoya (Bálint & Wojtusiak) and P. tegulina (Bálint et al). Our results highlight that an integrative approach is needed to clarify the taxonomy of these neotropical taxa, but more genetic and geographical studies are still required.