Inheritance-Based Diversity Measures for Explicit Convergence Control in Evolutionary Algorithms

Diversity is an important factor in evolutionary algorithms to prevent premature convergence towards a single local optimum. In order to maintain diversity throughout the process of evolution, various means exist in literature. We analyze approaches to diversity that (a) have an explicit and quantifiable influence on fitness at the individual level and (b) require no (or very little) additional domain knowledge such as domain-specific distance functions. We also introduce the concept of genealogical diversity in a broader study. We show that employing these approaches can help evolutionary algorithms for global optimization in many cases.Comment: GECCO '18: Genetic and Evolutionary Computation Conference, 2018, Kyoto, Japa

A Digital Twin framework for multi-objective optimization

This thesis represents the culmination of the Msc civil engineering course at the University of Agder. This thesis aims to attempt to define a framework for implementing digital twins in an investment cost/energy consumption optimization process. The methodology applied is a complex software hierarchy. The original dataset rests on randomly generated values of thermal transmittance, which are analysed in IDA ICE simulations, and compared to existing materials identified in the Norsk Prisbok for cost estimation. The results are optimized using a combination of Artificial Neural Networks and a multi-objective optimization algorithm, the elitist non-dominated sorting algorithm NSGA-II. The research question this thesis attempts to answer is: How can digital twins be implemented to reduce energy-consumption and costs in buildings? This thesis concludes that “A digital twin may be implemented to translate energy consumption and cost-optimization into an easily interpreted result that serves as a foundation for efficient decision-making.” This conclusion is based on the functionality of the various steps in the framework: Accuracy of ANN models, NSGA-II performance and visual presentation. The thesis presents a functional framework with a high degree of automation. Furthermore, applying said framework to a case study identified a potential energy consumption reduction of 35 % and a reduction in investment costs by 5 %

Reducing childhood illness - fostering growth : an integrated home-based intervention package (IHIP) to improve indoor-air pollution, drinking water quality and child nutrition

Child mortality attributable to pneumonia, diarrhoea and malnutrition accounts globally for the majority of 8.8 million annual deaths. More than half of these deaths are preventable. Available and effective interventions include safe water supply, household water treatment, improved chimney stoves and personal- and home-hygiene and -health messages. In Peru, the current health services reform is focused on shifting responsibilities to peripheral levels; thus, empowering community organisations to manage primary health care services, including health promotion and preventive measures at household level. The current political situation and policy framework to integrate effective preventive interventions that can be delivered at family level, prompted us to test the efficacy of a package of health interventions to reduce childhood illness burden at rural household level. The goal of this PhD thesis was to assess the efficacy of an Integrated Environmental Home-based-Intervention Package (IHIP), comprised of an improved chimney stoves, access to safe drinking water from solar radiation household water treatment (SODIS), and hygiene education interventions, to reduce morbidity of acute respiratory infections, diarrhoea and poor growth of rural Peruvian children under three years of age. We implemented a community-randomised control field trial (cRCT) in 51 community’s clusters of the San Marcos Province, Cajamarca Region, Peru. The cRCT was divided as follows: * Set-up, community selection and participatory intervention development: A pilot study was carried out for the selection of the interventions. These were adapted to local customs. The participatory phase is described in detail in Chapters 4 & 5. * Randomization, enrolment and baseline data collection: Chapter 6 describes the randomisation, enrolment and baseline in detail. * Carbon monoxide (CO) and Particulate Matter (PM2.5) household air quality assessment: Chapter 7 & 8 describe the efficacy of the OPTIMA-improved stove in improving household air quality in comparison to traditional open fire stoves. * Morbidity surveillance and field data acquisition: Morbidity data on the daily occurrence of signs and symptoms diarrhoea and respiratory illnesses of children was collected weekly. Anthropometric every two months and microbial data every 6 months. Chapter 9 describes the IHIP impact on morbidity reduction. * Workshops for a community-driven sustainable dessimination: Chapter 10 describes the community workshops and dissemination processes and dynamics within a socio-ecological framework. Our community-randomised control trial demonstrated that IHIP reduced 22% per year of child diarrhoea (RR 0.78, 95% CI: 0.49-1.05) and found an odds ratio of 0.71 for diarrhoea prevalence (OR 0.71, 95%, CI: 0.47, 1.06). No effects on the frequency of acute lower respiratory infections (RR 0.99, 95% CI: 0.59, 1.65) or child’s growth rates were found when comparing study arms. We identified three reasons for this moderate diarrhoea reduction: i) hand-washing promotion was universally found in our setting, since it is being promoted by the health care centre; ii) SODIS compliance was moderate: only one third of the beneficiaries were using the method regularly; and iii) the increased awareness for the child’s needs linked to the control intervention, could induce improved child care behaviour. The lack of effect on ALRI, could be linked to insufficient reduction in exposure to household air pollutants and high health service utilisation due to cultural beliefs and health seeking behavoiur. The household air pollution assessment study revealed only moderate reductions of 45% and 27% reduction of PM2.5 and CO, respectively for mothers’ personal exposure. This result was achieved in the best working stoves only. This may most likely not be sufficient to reduce impact on physician-diagnosed pneumonia. Community participatory meetings and surveys revealed that people’s decisions on adopting household-level environmental and hygiene interventions, was not only based on individual perceptions of their potential gains, but also depended on peer pressure and social network relations. Individual perceptions regarding pollution levels of water and household air (transparent, odourless water vs dirty air environments) influenced perceived gains and the adoption of certain interventions. Access to information and encouragement from health-care providers and programme implementers also increased adoption. The IHIP had several additional benefits beyond health outcomes. Mother’s expressed that the stoves could reduce cooking time and wood consumption, which translated into cost saving. They also could perform other task while cooking. Regarding the kitchen sink, the mothers expressed it facilitated handwashing, and washing of utensils with detergent, generating a cleaner kitchen environment that fostered home and food hygiene. We believe that the IHIP package motivated families to improve the kitchen living area in general. The high acceptance and sustained use was not only observed in the IHIP families but also in non-participating families that had copied the OPTIMA-improved stove after the community engagement in the desimination activities. We can also conclude that the IHIP package added to the family status, improved quality of life and impacted on their livelihoods, by empowering the beneficiary families. In conclusion, through this project we envisaged to demonstrate how an integrated package could be implemented at the household level in rural areas of Peru and its effect on health, quality of life and livelihoods. However, behaviour change for keeping maintanence of the interventions and use is necessary to achieve compliance, replication and sustainability

Dynamic Geometric Data Structures via Shallow Cuttings

We present new results on a number of fundamental problems about dynamic geometric data structures: 1) We describe the first fully dynamic data structures with sublinear amortized update time for maintaining (i) the number of vertices or the volume of the convex hull of a 3D point set, (ii) the largest empty circle for a 2D point set, (iii) the Hausdorff distance between two 2D point sets, (iv) the discrete 1-center of a 2D point set, (v) the number of maximal (i.e., skyline) points in a 3D point set. The update times are near n^{11/12} for (i) and (ii), n^{7/8} for (iii) and (iv), and n^{2/3} for (v). Previously, sublinear bounds were known only for restricted "semi-online" settings [Chan, SODA 2002]. 2) We slightly improve previous fully dynamic data structures for answering extreme point queries for the convex hull of a 3D point set and nearest neighbor search for a 2D point set. The query time is O(log^2n), and the amortized update time is O(log^4n) instead of O(log^5n) [Chan, SODA 2006; Kaplan et al., SODA 2017]. 3) We also improve previous fully dynamic data structures for maintaining the bichromatic closest pair between two 2D point sets and the diameter of a 2D point set. The amortized update time is O(log^4n) instead of O(log^7n) [Eppstein 1995; Chan, SODA 2006; Kaplan et al., SODA 2017]

Intelligent systems in manufacturing: current developments and future prospects

Global competition and rapidly changing customer requirements are demanding increasing changes in manufacturing environments. Enterprises are required to constantly redesign their products and continuously reconfigure their manufacturing systems. Traditional approaches to manufacturing systems do not fully satisfy this new situation. Many authors have proposed that artificial intelligence will bring the flexibility and efficiency needed by manufacturing systems. This paper is a review of artificial intelligence techniques used in manufacturing systems. The paper first defines the components of a simplified intelligent manufacturing systems (IMS), the different Artificial Intelligence (AI) techniques to be considered and then shows how these AI techniques are used for the components of IMS

Brain Shape Convergence In The Adaptive Radiation Of New World Monkeys

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Primates constitute one of the most diverse mammalian clades, and a notable feature of their diversification is the evolution of brain morphology. However, the evolutionary processes and ecological factors behind these changes are largely unknown. In this work, we investigate brain shape diversification of New World monkeys during their adaptive radiation in relation to different ecological dimensions. Our results reveal that brain diversification in this clade can be explained by invoking a model of adaptive peak shifts to unique and shared optima, defined by a multidimensional ecological niche hypothesis. Particularly, we show that the evolution of convergent brain phenotypes may be related to ecological factors associated with group size (e.g., social complexity). Together, our results highlight the complexity of brain evolution and the ecological significance of brain shape changes during the evolutionary diversification of a primate clade.113821582163Fondo para la Investigacion Cientifica y TecnologicaConselho Nacional de Desenvolvimento Cientifico e TecnologicoFundacao de Amparo a Pesquisa do Estado de Sao PauloConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP

Brain shape convergence in the adaptive radiation of New World monkeys

Primates constitute one of the most diverse mammalian clades, and a notable feature of their diversification is the evolution of brain morphology. However, the evolutionary processes and ecological factors behind these changes are largely unknown. In this work, we investigate brain shape diversification of New World monkeys during their adaptive radiation in relation to different ecological dimensions. Our results reveal that brain diversification in this clade can be explained by invoking a model of adaptive peak shifts to unique and shared optima, defined by a multidimensional ecological niche hypothesis. Particularly, we show that the evolution of convergent brain phenotypes may be related to ecological factors associated with group size (e.g., social complexity). Together, our results highlight the complexity of brain evolution and the ecological significance of brain shape changes during the evolutionary diversification of a primate clade.Facultad de Ciencias Naturales y Muse

XV OPTIMA MEETING, Montpellier (France), 6-11 June 2016, Abstracts

Book of abstract of the XV OPTIMA MEETING held in Montpellier (France) from 6th to 11th June 201