Non-smooth optimization methods for computation of the conditional value-at-risk and portfolio optimization

We examine numerical performance of various methods of calculation of the Conditional Value-at-risk (CVaR), and portfolio optimization with respect to this risk measure. We concentrate on the method proposed by Rockafellar and Uryasev in (Rockafellar, R.T. and Uryasev, S., 2000, Optimization of conditional value-at-risk. Journal of Risk, 2, 21-41), which converts this problem to that of convex optimization. We compare the use of linear programming techniques against a non-smooth optimization method of the discrete gradient, and establish the supremacy of the latter. We show that non-smooth optimization can be used efficiently for large portfolio optimization, and also examine parallel execution of this method on computer clusters.<br /

Parallelization of the discrete gradient method of non-smooth optimization and its applications

We investigate parallelization and performance of the discrete gradient method of nonsmooth optimization. This derivative free method is shown to be an effective optimization tool, able to skip many shallow local minima of nonconvex nondifferentiable objective functions. Although this is a sequential iterative method, we were able to parallelize critical steps of the algorithm, and this lead to a significant improvement in performance on multiprocessor computer clusters. We applied this method to a difficult polyatomic clusters problem in computational chemistry, and found this method to outperform other algorithms. <br /

Single - particle correlations in events with the total disintegration of nuclei

New experimental data on the behaviour of the single-particle two-dimensional correlation functions R versus Q (Q is the number of nucleons emitted from nuc- lei) and Ap (Ap is the mass of projectile nuclei) are presented in this paper. The interactions of protons, d, 4He and 12C nuclei with carbon nuclei (at a momentum of 4.2 A GeV/c) are considered.The values of R are obtained separately for pi minus mesons and protons.In so doing,the values of R are normalized so that -1=<R=<1.The value of R=0 corresponds to the case of the absence of corre- lations.It has been found that the Q- and Ap-dependence of R takes place only for weak correlations (R< 0.3).In the main (90 %),these correlations are con- nected with the variable pt and have a nonlinear character, that is the regi- ons with different characters of the Q-dependence of R are separated: there is a change of regimes in the Q-dependences of R.The correlations weaken with increasing Ap, and the variable R gets the least values of all the considered ones in 12CC interactions.Simultaneously with weakening the correlations in the region of large Q, the character of the Q-dependence of R changes.Comment: 17 pages, submitted to Phys. Rew.

New data on the distribution of digger wasps of the genus Ammophila W. Kirby, 1798 (Hymenoptera, Sphecidae)

An annotated list is given and the distribution of five species of digger wasps genus Ammophila, collected in the circumpolar regions of Western Siberia (in the Yamalo-Nenets Autonomous District) in 2017, is specified

A simulated annealing-based maximum-margin clustering algorithm

© 2018 Wiley Periodicals, Inc. Maximum-margin clustering is an extension of the support vector machine (SVM) to clustering. It partitions a set of unlabeled data into multiple groups by finding hyperplanes with the largest margins. Although existing algorithms have shown promising results, there is no guarantee of convergence of these algorithms to global solutions due to the nonconvexity of the optimization problem. In this paper, we propose a simulated annealing-based algorithm that is able to mitigate the issue of local minima in the maximum-margin clustering problem. The novelty of our algorithm is twofold, ie, (i) it comprises a comprehensive cluster modification scheme based on simulated annealing, and (ii) it introduces a new approach based on the combination of k-means++ and SVM at each step of the annealing process. More precisely, k-means++ is initially applied to extract subsets of the data points. Then, an unsupervised SVM is applied to improve the clustering results. Experimental results on various benchmark data sets (of up to over a million points) give evidence that the proposed algorithm is more effective at solving the clustering problem than a number of popular clustering algorithms

Interaction of microplastics and terrestrial and aquatic insects (bioaccumulation, degradation, ecotoxicological effects)

World production of convenient and durable materials made of synthetic plastics during the last 70 years caused the dispersal of microplastic particles in the environment. Microplastic pollution is the focus of interest worldwide due to its global distribution and adverse effects on living organisms. The largest number of studies addressing this issue explored the aquatic environment, yet terrestrial ecosystems also suffer from microplastic pollution. Insects are crucial for most terrestrial ecosystems. Few can compete with them in biomass productivity and species diversity, which makes them targets for studying the toxic bioaccumulation. This review article presents a systematic analysis of data on bioaccumulation, degradation of microplastics by aquatic and terrestrial entomofauna, and its ecotoxicological effects

Suitability and managerial implications of a Master Surgical Scheduling approach

Abstract: Operating room (OR) planning and scheduling is a popular and challenging subject within the operational research applied to health services research (ORAHS). However, the impact in practice is very limited. The organization and culture of a hospital and the inherent characteristics of its processes impose specific implementation issues that affect the success of planning approaches. Current tactical OR planning approaches often fail to account for these issues.Master surgical scheduling (MSS) is a promising approach for hospitals to optimize resource utilization and patient flows. We discuss the pros and cons of MSS and compare MSS with centralized and decentralized planning approaches. Finally, we address various implementation issues of MSS and discuss its suitability for hospitals with different organizational foci and culture

The Resource Curse and Rentier States in the Caspian Region : A Need for Context Analysis

Although much attention is paid to the Caspian region with regard to energy issues, the domestic consequences of the region’s resource production have so far constituted a neglected field of research. A systematic survey of the latest research trends in the economic and political causalities of the resource curse and of rentier states reveals that there is a need for context analysis. In reference to this, the paper traces any shortcomings and promising approaches in the existent body of literature on the Caspian region. Following on from this, the paper then proposes a new approach; specifically, one in which any differences and similarities in the context conditions are captured. This enables a more precise exploration of the exact ways in which they form contemporary post-Soviet Caspian rentier states.Obwohl der Region am Kaspischen Meer im Zuge von Energiediskursen große Aufmerksamkeit zuteil wird, stellen die innerstaatlichen Folgen der Ressourcenproduktion in der Region ein bislang vernachlässigtes Forschungsfeld dar. Ein systematischer Überblick über die jüngsten Forschungstrends zu wirtschaftlichen und politischen Kausalzusammenhängen des Ressourcenfluchs und zu Rentierstaaten offenbart die Notwendigkeit von Kontextanalysen. Hierauf Bezug nehmend, analysiert der Aufsatz sowohl die Mängel als auch viel versprechende Ansätze in der betreffenden Literatur zur Region am Kaspischen Meer. Der Aufsatz stellt letztendlich einen neuen Ansatz vor, der Unterschiede und Gemeinsamkeiten in den Kontextbedingungen erfasst, um zu erforschen, wie diese die gegenwärtigen post-sowjetischen Rentierstaaten in der Region am Kaspischen Meer tatsächlich prägen