Evidence for genetic differentiation of Octopus vulgaris (Mollusca, Cephalopoda) fishery populations from the southern coast of Brazil as revealed by microsatellites

Octopus vulgaris is a cephalopod species in several oceans and commonly caught by artisanal and industrial fisheries. In Brazil, O. vulgaris populations are mainly distributed along the southern coast and have been subjected to intensive fishing during recent years. Despite the importance of this marine resource, no genetic study has been carried out to examine genetic differences among populations along the coast of Brazil. In this study, 343 individuals collected by commercial vessels were genotyped at six microsatellite loci to investigate the genetic differences in O. vulgaris populations along the southern coast of Brazil. Genetic structure and levels of differentiation among sampling sites were estimated via a genotype assignment test and F-statistics. Our results indicate that the O. vulgaris stock consists of four genetic populations with an overall significant analogous F(ST). (phi(CT) = 0.10710, P<0.05) value. The genetic diversity was high with an observed heterozygosity of Ho = 0.987. The negative values of F(IS) found for most of the loci examined suggested a possible bottleneck process. These findings are important for further steps toward more sustainable octopus fisheries, so that this marine resource can be preserved for long-term utilization. (C) 2011 Elsevier B.V. All rights reserved.

Simple heuristics for the assembly line worker assignment and balancing problem

We propose simple heuristics for the assembly line worker assignment and balancing problem. This problem typically occurs in assembly lines in sheltered work centers for the disabled. Different from the well-known simple assembly line balancing problem, the task execution times vary according to the assigned worker. We develop a constructive heuristic framework based on task and worker priority rules defining the order in which the tasks and workers should be assigned to the workstations. We present a number of such rules and compare their performance across three possible uses: as a stand-alone method, as an initial solution generator for meta-heuristics, and as a decoder for a hybrid genetic algorithm. Our results show that the heuristics are fast, they obtain good results as a stand-alone method and are efficient when used as a initial solution generator or as a solution decoder within more elaborate approaches.