One PLOT to Show Them All: Visualization of Efficient Sets in Multi-Objective Landscapes

Visualization techniques for the decision space of continuous multi-objective optimization problems (MOPs) are rather scarce in research. For long, all techniques focused on global optimality and even for the few available landscape visualizations, e.g., cost landscapes, globality is the main criterion. In contrast, the recently proposed gradient field heatmaps (GFHs) emphasize the location and attraction basins of local efficient sets, but ignore the relation of sets in terms of solution quality. In this paper, we propose a new and hybrid visualization technique, which combines the advantages of both approaches in order to represent local and global optimality together within a single visualization. Therefore, we build on the GFH approach but apply a new technique for approximating the location of locally efficient points and using the divergence of the multi-objective gradient vector field as a robust second-order condition. Then, the relative dominance relationship of the determined locally efficient points is used to visualize the complete landscape of the MOP. Augmented by information on the basins of attraction, this Plot of Landscapes with Optimal Trade-offs (PLOT) becomes one of the most informative multi-objective landscape visualization techniques available.Comment: This version has been accepted for publication at the 16th International Conference on Parallel Problem Solving from Nature (PPSN XVI

Globally convergent evolution strategies for constrained optimization

International audienceIn this paper we propose, analyze, and test algorithms for constrained optimization when no use of derivatives of the objective function is made. The proposed methodology is built upon the globally convergent evolution strategies previously introduced by the authors for unconstrained optimization. Two approaches are encompassed to handle the constraints. In a first approach, feasibility is first enforced by a barrier function and the objective function is then evaluated directly at the feasible generated points. A second approach projects first all the generated points onto the feasible domain before evaluating the objective function.The resulting algorithms enjoy favorable global convergence properties (convergence to stationarity from arbitrary starting points), regardless of the linearity of the constraints.The algorithmic implementation (i) includes a step where previously evaluated points are used to accelerate the search (by minimizing quadratic models) and (ii) addresses the particular cases of bounds on the variables and linear constraints. Our solver is compared to others, and the numerical results confirm its competitiveness in terms of efficiency and robustness

Development of premature children: caregivers' understanding according to the Bioecological Theory

Abstract OBJECTIVE Understanding the conceptions of premature children caregivers on child development and associated factors. METHOD An exploratory-descriptive qualitative study of 12 families with children under three years of age. Interviews were submitted to thematic content analysis, systematized into the categories of Bioecological Theory of Human Development: Process, Person, Context and Time, and in the Functional Development category. RESULTS There are concerns about impairment in the current and future development of a Person/child defined as fragile as a result of premature birth (Time dimension), minimized by the scope of observable competencies such as motor skills. The Context, especially family and health services, and Proximal Processes, described as one-way caregiver interactions, are considered determinants of development. Functional Development is considered a natural consequence and result of education. The support network is crucial, supporting or limiting care. CONCLUSION Concerns about the development mobilize caregivers to stimulate the premature child/person and requests family and healthcare assistance

CEO Profile and Earnings Quality

This paper introduces the PSCORE, which aggregates nine personal characteristics of chief executive officers (CEOs), to signal the quality of earnings. The PSCORE is a composite score based on publicly available data on CEOs. The study reports strong positive relationships between the PSCORE and two different proxies for earnings quality, (i) discretionary accruals and (ii) financial statement errors, measured by deviations of the first digits of figures reported in financial statements from those expected by Benford’s Law. Further analyses indicate that the relationships between the PSCORE and the proxies for earnings quality become more pronounced when CEOs have high equity-based compensation incentives. The findings have some implications for practitioners

Precise determination of the mass of the Higgs boson and tests of compatibility of its couplings with the standard model predictions using proton collisions at 7 and 8 TeV

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Measurement of prompt J/ψ pair production in pp collisions at √s = 7 Tev

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Search for Dark Matter and Supersymmetry with a Compressed Mass Spectrum in the Vector Boson Fusion Topology in Proton-Proton Collisions at root s=8 TeV

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Search for neutral MSSM Higgs bosons decaying to a pair of tau leptons in pp collisions

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