Particle Swarm Optimization with non-smooth penalty reformulation for a complex portfolio selection problem

In the classical model for portfolio selection the risk is measured by the variance of returns. It is well known that, if returns are not elliptically distributed, this may cause inaccurate investment decisions. To address this issue, several alternative measures of risk have been proposed. In this contribution we focus on a class of measures that uses information contained both in lower and in upper tail of the distribution of the returns. We consider a nonlinear mixed-integer portfolio selection model which takes into account several constraints used in fund management practice. The latter problem is NP-hard in general, and exact algorithms for its minimization, which are both effective and efficient, are still sought at present. Thus, to approximately solve this model we experience the heuristics Particle Swarm Optimization (PSO). Since PSO was originally conceived for unconstrained global optimization problems, we apply it to a novel reformulation of our mixed-integer model, where a standard exact penalty function is introduced.Portfolio selection, coherent risk measure, fund management constraints, NP-hard mathematical programming problem, PSO, exact penalty method, SP100 index's assets.

Average Rate of Downlink Heterogeneous Cellular Networks over Generalized Fading Channels - A Stochastic Geometry Approach

In this paper, we introduce an analytical framework to compute the average rate of downlink heterogeneous cellular networks. The framework leverages recent application of stochastic geometry to other-cell interference modeling and analysis. The heterogeneous cellular network is modeled as the superposition of many tiers of Base Stations (BSs) having different transmit power, density, path-loss exponent, fading parameters and distribution, and unequal biasing for flexible tier association. A long-term averaged maximum biased-received-power tier association is considered. The positions of the BSs in each tier are modeled as points of an independent Poisson Point Process (PPP). Under these assumptions, we introduce a new analytical methodology to evaluate the average rate, which avoids the computation of the Coverage Probability (Pcov) and needs only the Moment Generating Function (MGF) of the aggregate interference at the probe mobile terminal. The distinguishable characteristic of our analytical methodology consists in providing a tractable and numerically efficient framework that is applicable to general fading distributions, including composite fading channels with small- and mid-scale fluctuations. In addition, our method can efficiently handle correlated Log-Normal shadowing with little increase of the computational complexity. The proposed MGF-based approach needs the computation of either a single or a two-fold numerical integral, thus reducing the complexity of Pcov-based frameworks, which require, for general fading distributions, the computation of a four-fold integral.Comment: Accepted for publication in IEEE Transactions on Communications, to appea

Beyond the adjacent possible: On the irreducibility of human creativity to biology and physics

In this article, the problem of understanding multiple layers of complexity in our universe is addressed, with particular emphasis on explaining creative evolutions in the material, biological, and psycho-social layers. Perspectives from physics, biology, psychology, and philosophy are utilized in the discussion. Process philosophy is used to justify the theoretical foundation of the dynamic universal creativity process. The concepts of unified and final theories are discussed from a position that criticizes reductionism. The concept of the adjacent possible is reviewed as introduced by Kauffman to exclude the possibility that a theory from physics could be extended to explain the biological layer. In a similar way, the adjacent possible is shown to be useful but insufficient to explain the psycho-social layer of complexity, missing fundamental human abilities such as thinking of long-term futures, wisdom, and dynamic creativity leaps that use the impossible as an inspiration

Novel Psychaoctive Sucbstances and Behavioural Addictions

Copyright © 2014 Giovanni Martinotti et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Date of Acceptance: 09/11/2014Peer reviewedFinal Published versio

Potential Originality and Effectiveness: The Dynamic Definition of Creativity

Given the central role of creativity in the future post-information society, a call for a pragmatist approach to the study of creativity is advocated, that brings as a consequence the recognition of the dynamic nature of this phenomenon. At the foundation of the proposed new theoretical framework lies the definition of creativity itself, which is turned from static to dynamic through the introduction of the concept of potential originality and effectiveness. Starting from this central definition, and through the introduction of the auxiliary definitions for focus area, creativity goal, creative agent, creative potential of an agent, creative potential of an environment, creative process, product of a creative process, creativity potential of a process, representation of the product of a creative process, and estimator, we arrive at the definitions of creative achievement and creative inconclusiveness. Although both aspects are key in the creative process, creative inconclusiveness was not part of previous definitions, but it is argued that its role is fundamental for effective education in creativity. The new definitions are shown to have full backward compatibility with the extant corpus of scientific research in creativity, as well as forward effectiveness in suggesting novel investigation approaches to support the consideration of new theoretical hypotheses

An Artificial Neural Network technique for on-line hotel booking

In this paper the use of Artificial Neural Networks (ANNs) in on-line booking for hotel industry is investigated. The paper details the description, the modeling and the resolution technique of on-line booking. The latter problem is modeled using the paradigms of machine learning, in place of standard `If-Then-Else' chains of conditional rules. In particular, a supervised three layers MLP neural network is adopted, which is trained using information from previous customers' reservations. Performance of our ANN is analyzed: it behaves in a quite satisfactory way in managing the (simulated) booking service in a hotel. The customer requires single or double rooms, while the system gives as a reply the confirmation of the required services, if available. Moreover, we highlight that using our approach the system proposes alternative accommodations (from two days in advance to two days later with respect to the requested day), in case rooms or services are not available. Numerical results are given, where the effectiveness of the proposed approach is critically analyzed. Finally, we outline guidelines for future research.On-line booking; hotel reservation; machine learning; supervised multilayer perceptron networks

Intelligence and Creativity: Mapping Constructs on the Space-Time Continuum

This theoretical article proposes a unified framework of analysis for the constructs of intelligence and creativity. General definitions for intelligence and creativity are provided, allowing fair comparisons between the two context-embedded constructs. A novel taxonomy is introduced to classify the contexts in which intelligent and/or creative behavior can be embedded, in terms of the tightness vs. looseness of the relevant conceptual space S and available time T. These two dimensions are used to form what is identified as the space-time continuum, containing four quadrants: tight space and tight time, loose space and tight time, tight space and loose time, loose space and loose time. The intelligence and creativity constructs can be mapped onto the four quadrants and found to overlap more or less, depending on the context characteristics. Measurement methodologies adapted to the four different quadrants are discussed. The article concludes with a discussion about future research directions based on the proposed theoretical framework, in terms of theories and hypotheses on intelligence and creativity, of eminent personalities and personality traits, as well as its consequences for developmental, educational, and professional environments

TRIZ as Seen through the DIMAI Creative Thinking Model

Abstract The aim of this paper is to show that TRIZ is not an isolated theory, but a set of tools that can be interpreted in the light of general theoretical models for creativity. In fact, the numerous tools and strategies that TRIZ formulates can be seen as specific instances of the DIMAI model for the creative thinking process, which takes into account environmental, personality, and cognitive factors and postulates five principal states: Drive, Information, Movement, Assessment and Implementation. Letting "strategy" be defined as a sequence of activation of states, components or sub-processes that includes implementation as a final step, we show how TRIZ offers a systematic organization of strategies for the disciplined and aware use of the complex interactions between the cognitive, individual and emotional elements hypothesized into the DIMAI model. The interpretation of TRIZ through the DIMAI model is not only interesting from a theoretical point of view, but it adds an awareness layer which can help both the scientist and the practitioner in dealing systematically and homogeneously with the multiple variables and elements involved in the creative and innovative act, thus enhancing the overall effectiveness

An Artificial Neural Network-based technique for on-line hotel booking

AbstractIn this paper the use of Artificial Neural Networks (ANNs) in on-line booking for hotel industry is investigated. The paper details the description, the modeling and the resolution technique of on-line booking. The latter problem is modeled using the paradigms of machine learning, in place of standard 'If-Then-Else' chains of conditional rules. In particular, a supervised three layers MultiLayer Perceptron (MLP) ANN is adopted, which is trained using information from previous customers' reservations. Performances of our ANNs are analyzed: they behave in a quite satisfactory way in managing the (simulated) booking service in a hotel. The customer requires single or double rooms, while the system gives as a reply the confirmation of the required services, if available. Moreover, in the case rooms or services are not at disposal, we highlight that using our approach the system proposes alternative accommodations (from two days in advance to two days later with respect to the requested day). Numerical results are given, where the effectiveness of the proposed approach is critically analyzed. Finally, we outline guidelines for future research

Windowed Decoding of Protograph-based LDPC Convolutional Codes over Erasure Channels

We consider a windowed decoding scheme for LDPC convolutional codes that is based on the belief-propagation (BP) algorithm. We discuss the advantages of this decoding scheme and identify certain characteristics of LDPC convolutional code ensembles that exhibit good performance with the windowed decoder. We will consider the performance of these ensembles and codes over erasure channels with and without memory. We show that the structure of LDPC convolutional code ensembles is suitable to obtain performance close to the theoretical limits over the memoryless erasure channel, both for the BP decoder and windowed decoding. However, the same structure imposes limitations on the performance over erasure channels with memory.Comment: 18 pages, 9 figures, accepted for publication in the IEEE Transactions on Information Theor