Good practice proposal for the implementation, presentation, and comparison of metaheuristics for solving routing problems

Researchers who investigate in any area related to computational algorithms (both dening new algorithms or improving existing ones) usually nd large diculties to test their work. Comparisons among dierent researches in this eld are often a hard task, due to the ambiguity or lack of detail in the presentation of the work and its results. On many occasions, the replication of the work conducted by other researchers is required, which leads to a waste of time and a delay in the research advances. The authors of this study propose a procedure to introduce new techniques and their results in the eld of routing problems. In this paper this procedure is detailed, and a set of good practices to follow are deeply described. It is noteworthy that this procedure can be applied to any combinatorial optimization problem. Anyway, the literature of this study is focused on routing problems. This eld has been chosen because of its importance in real world, and its relevance in the actual literature

Crossover versus Mutation: A Comparative Analysis of the Evolutionary Strategy of Genetic Algorithms Applied to Combinatorial Optimization Problems

Since their first formulation, genetic algorithms (GAs) have been one of the most widely used techniques to solve combinatorial optimization problems. The basic structure of the GAs is known by the scientific community, and thanks to their easy application and good performance, GAs are the focus of a lot of research works annually. Although throughout history there have been many studies analyzing various concepts of GAs, in the literature there are few studies that analyze objectively the influence of using blind crossover operators for combinatorial optimization problems. For this reason, in this paper a deep study on the influence of using them is conducted. The study is based on a comparison of nine techniques applied to four well-known combinatorial optimization problems. Six of the techniques are GAs with different configurations, and the remaining three are evolutionary algorithms that focus exclusively on the mutation process. Finally, to perform a reliable comparison of these results, a statistical study of them is made, performing the normal distribution z-test

Crossover vs. Mutation: A Comparative Analysis of the Evolutionary Strategy of Genetic Algorithms Applied to Combinatorial Optimization Problems

Since their first formulation, genetic algorithms (GA) have been one of the most widely used techniques to solve combinatorial optimization problems. The basic structure of the GA is known by the scientific community, and thanks to their easy application and good performance, GAs are the focus of a lot of research works annually. Although throughout history there have been many studies analyzing various concepts of GAs, in the literature there are few studies that analyze objectively the influence of using blind crossover operators for combinatorial optimization problems. For this reason, in this paper a deep study on the influence of using them is conducted. The study is based on a comparison of nine techniques applied to four well-known combinatorial optimization problems. Six of the techniques are GAs with different configurations, and the remaining three are evolutionary algorithms that focus exclusively on the mutation process. Finally, to perform a reliable comparison of these results, a statistical study of them is made, performing the normal distribution z-test

Expression of glucocorticoid inducible genes is associated with reductions in cornu ammonis and dentate gyrus volumes in patients with major depressive disorder

Alterations of the glucocorticoid system and of hippocampal volumes have consistently been reported in patients with major depressive disorders (MDD). The aim of the present study was to investigate whether the messenger RNA (mRNA) expression of glucocorticoid inducible genes is associated with changes in the cornu ammonis (CA) and dentate gyrus subfields. Forty-three patients with MDD and 43 healthy controls were recruited and investigated with high resolution magnetic resonance imaging. Hippocampal subfields were measured using freesurfer. Measurement of whole blood mRNA expression of glucocorticoid inducible genes serum and glucocorticoid-regulated kinase 1 (SGK1), FK506 binding protein 5 (FKBP5), and glucocorticoid induced leucine zipper (GILZ) was performed. Patients with MDD had significantly smaller volumes of CA1, CA2/3, CA4/DG, and subiculum compared to healthy controls. In the regression analysis, the factor diagnosis had a significant moderating effect on the association of SGK1 and hippocampal volumes. Patients with low expression of SGK1 had significantly smaller CA2/3 and CA4/DG volumes compared to patients with high expression of SGK1 mRNA and to healthy controls with low/high expression of SGK1, respectively. Therefore, a lack of mRNA expression of glucocorticoid inducible genes in patients with MDD that seems to correspond to a blunted cortisol response is associated with smaller hippocampal CA and dentate gyrus volumes. SGK1 seems to be particularly relevant for stress-related mental disorders

Multi-site genetic analysis of diffusion images and voxelwise heritability analysis : a pilot project of the ENIGMA–DTI working group

The ENIGMA (Enhancing NeuroImaging Genetics through Meta-Analysis) Consortium was set up to analyze brain measures and genotypes from multiple sites across the world to improve the power to detect genetic variants that influence the brain. Diffusion tensor imaging (DTI) yields quantitative measures sensitive to brain development and degeneration, and some common genetic variants may be associated with white matter integrity or connectivity. DTI measures, such as the fractional anisotropy (FA) of water diffusion, may be useful for identifying genetic variants that influence brain microstructure. However, genome-wide association studies (GWAS) require large populations to obtain sufficient power to detect and replicate significant effects, motivating a multi-site consortium effort. As part of an ENIGMA–DTI working group, we analyzed high-resolution FA images from multiple imaging sites across North America, Australia, and Europe, to address the challenge of harmonizing imaging data collected at multiple sites. Four hundred images of healthy adults aged 18–85 from four sites were used to create a template and corresponding skeletonized FA image as a common reference space. Using twin and pedigree samples of different ethnicities, we used our common template to evaluate the heritability of tract-derived FA measures. We show that our template is reliable for integrating multiple datasets by combining results through meta-analysis and unifying the data through exploratory mega-analyses. Our results may help prioritize regions of the FA map that are consistently influenced by additive genetic factors for future genetic discovery studies. Protocols and templates are publicly available at (http://enigma.loni.ucla.edu/ongoing/dti-working-group/)

Brain structural abnormalities in obesity: relation to age, genetic risk, and common psychiatric disorders: evidence through univariate and multivariate mega-analysis including 6420 participants from the ENIGMA MDD working group

Published online: 28 May 2020Emerging evidence suggests that obesity impacts brain physiology at multiple levels. Here we aimed to clarify the relationship between obesity and brain structure using structural MRI (n = 6420) and genetic data (n = 3907) from the ENIGMA Major Depressive Disorder (MDD) working group. Obesity (BMI > 30) was significantly associated with cortical and subcortical abnormalities in both mass-univariate and multivariate pattern recognition analyses independent of MDD diagnosis. The most pronounced effects were found for associations between obesity and lower temporo-frontal cortical thickness (maximum Cohen´s d (left fusiform gyrus) = −0.33). The observed regional distribution and effect size of cortical thickness reductions in obesity revealed considerable similarities with corresponding patterns of lower cortical thickness in previously published studies of neuropsychiatric disorders. A higher polygenic risk score for obesity significantly correlated with lower occipital surface area. In addition, a significant age-by-obesity interaction on cortical thickness emerged driven by lower thickness in older participants. Our findings suggest a neurobiological interaction between obesity and brain structure under physiological and pathological brain conditions.Nils Opel ... Bernhard T. Baune ... et al

Frontal lobe changes occur early in the course of affective disorders in young people

<p>Abstract</p> <p>Background</p> <p>More severe and persistent forms of affective disorders are accompanied by grey matter loss in key frontal and temporal structures. It is unclear whether such changes precede the onset of illness, occur early in the course or develop gradually with persistence or recurrence of illness. A total of 47 young people presenting with admixtures of depressive and psychotic symptoms were recruited from specialist early intervention services along with 33 age matched healthy control subjects. All participants underwent magnetic resonance imaging and patients were rated clinically as to current stage of illness. Twenty-three patients were identified as being at an early 'attenuated syndrome' stage, while the remaining were rated as having already reached the 'discrete disorder' or 'persistent or recurrent illness' stage. Contrasts were carried out between controls subjects and patients cohorts with attenuated syndromes and discrete disorders, separately.</p> <p>Results</p> <p>The patients that were identified as having a discrete or persisting disorder demonstrated decreased grey matter volumes within distributed frontal brain regions when contrasted to both the control subjects as well as those patients in the attenuated syndrome stage. Overall, patients who were diagnosed as more advanced in terms of the clinical stage of their illness, exhibited the greatest grey matter volume loss of all groups.</p> <p>Conclusions</p> <p>This study suggests that, in terms of frontal grey matter changes, a major transition point may occur in the course of affective illness between early attenuated syndromes and later discrete illness stages.</p

Brain structural correlates of insomnia severity in 1053 individuals with major depressive disorder : results from the ENIGMA MDD Working Group

It has been difficult to find robust brain structural correlates of the overall severity of major depressive disorder (MDD). We hypothesized that specific symptoms may better reveal correlates and investigated this for the severity of insomnia, both a key symptom and a modifiable major risk factor of MDD. Cortical thickness, surface area and subcortical volumes were assessed from T1-weighted brain magnetic resonance imaging (MRI) scans of 1053 MDD patients (age range 13-79 years) from 15 cohorts within the ENIGMA MDD Working Group. Insomnia severity was measured by summing the insomnia items of the Hamilton Depression Rating Scale (HDRS). Symptom specificity was evaluated with correlates of overall depression severity. Disease specificity was evaluated in two independent samples comprising 2108 healthy controls, and in 260 clinical controls with bipolar disorder. Results showed that MDD patients with more severe insomnia had a smaller cortical surface area, mostly driven by the right insula, left inferior frontal gyrus pars triangularis, left frontal pole, right superior parietal cortex, right medial orbitofrontal cortex, and right supramarginal gyrus. Associations were specific for insomnia severity, and were not found for overall depression severity. Associations were also specific to MDD; healthy controls and clinical controls showed differential insomnia severity association profiles. The findings indicate that MDD patients with more severe insomnia show smaller surfaces in several frontoparietal cortical areas. While explained variance remains small, symptom-specific associations could bring us closer to clues on underlying biological phenomena of MDD

No Alterations of Brain Structural Asymmetry in Major Depressive Disorder: An ENIGMA Consortium Analysis

OBJECTIVE: Asymmetry is a subtle but pervasive aspect of the human brain, and it may be altered in several psychiatric conditions. MRI studies have shown subtle differences of brain anatomy between people with major depressive disorder and healthy control subjects, but few studies have specifically examined brain anatomical asymmetry in relation to this disorder, and results from those studies have remained inconclusive. At the functional level, some electroencephalography studies have indicated left fronto-cortical hypoactivity and right parietal hypoactivity in depressive disorders, so aspects of lateralized anatomy may also be affected. The authors used pooled individual-level data from data sets collected around the world to investigate differences in laterality in measures of cortical thickness, cortical surface area, and subcortical volume between individuals with major depression and healthy control subjects. METHODS: The authors investigated differences in the laterality of thickness and surface area measures of 34 cerebral cortical regions in 2,256 individuals with major depression and 3,504 control subjects from 31 separate data sets, and they investigated volume asymmetries of eight subcortical structures in 2,540 individuals with major depression and 4,230 control subjects from 32 data sets. T1-weighted MRI data were processed with a single protocol using FreeSurfer and the Desikan-Killiany atlas. The large sample size provided 80% power to detect effects of the order of Cohen's d=0.1. RESULTS: The largest effect size (Cohen's d) of major depression diagnosis was 0.085 for the thickness asymmetry of the superior temporal cortex, which was not significant after adjustment for multiple testing. Asymmetry measures were not significantly associated with medication use, acute compared with remitted status, first episode compared with recurrent status, or age at onset. CONCLUSIONS: Altered brain macro-anatomical asymmetry may be of little relevance to major depression etiology in most cases