For CVaR portfolio nonsmooth optimization problem, we propose an infeasible incremental bundle method on the basis of the improvement function and the main idea of incremental method for solving convex finite min-max problems. The presented algorithm only employs the information of the objective function and one component function of constraint functions to form the approximate model for improvement function. By introducing the aggregate technique, we keep the information of previous iterate points that may be deleted from bundle to (...) overcome the difficulty of numerical computation and storage. Our algorithm does not enforce the feasibility of iterate points and the monotonicity of objective function, and the global convergence of the algorithm is established under mild conditions. Compared with the available results, our method loosens the requirements of computing the whole constraint function, which makes the algorithm easier to implement. (shrink)

This paper uses two techniques to build a socially responsible portfolio of U.S. equities and examines prospective performance using publicly available data. The first technique eliminates stocks from consideration using categorical exclusions with a restrictive Environment, Social and Governance screen. The paper shows that stocks surviving the screen have a significantly higher average projected Value Line alpha and are more likely to have a Morningstar 5-star rating. Using categorical exclusions, however, introduces a sector bias in that the ESG screen (...) is more likely to restrict stocks from the manufacturing sector than the service sector. The second technique does not introduce a sector bias because it uses a best-in-class optimization approach in place of screening. The paper introduces a linear programming model called Data Envelopment Analysis to the application of SRI portfolio development to find the best financially and socially performing companies within each industry sector. When compared to a categorical exclusions portfolio, a DEA portfolio is rated significantly higher by Morningstar and Value Line. Depending on the specific needs of a socially responsible investor, the DEA technique could be a better tool in developing a financially and socially balanced equity portfolio. (shrink)

Optimization and Stochastic Processes Applied to Economy and Finance. Textbook for the BM&F-USP (Brazilian Mercantile and Futures Exchange - University of Sao Paulo) Master's degree program in Finance.

In the financial markets, there is a well established portfolio optimization model called generalized mean-variance model (or generalized Markowitz model). This model considers that a typical investor, while expecting returns to be high, also expects returns to be as certain as possible. In this paper we introduce a new media optimization system based on the mean-variance model, a novel approach in media planning. After presenting the model in its full generality, we discuss possible advantages of the mean-variance (...) paradigm, such as its flexibility in modeling the optimization problem, its ability of dealing with many media performance indices – satisfying most of the media plan needs – and, most important, the property of diversifying the media portfolios in a natural way, without the need to set up ad hoc constraints to enforce diversification. (shrink)

The question posed is whether the optimization methods of calculus that are often used in social and scientific analyses offer an appropriate analytical approach to analyze problems that are immersed in systemic complexity and its consequences. This paper refers to the portfolio of such complex problems belonging to social and scientific forces. We refer to such a complex combination by the term ‘socio-scientific’. In the study of socio-scientific complexity, dynamic preferences, intricate decisions, and uncertain behavior, endogenous relations and (...) systemic perturbations abound. The arguments presented in this paper establish that the methodological approach of optimization and steady-state equilibrium turns out to be nicety rather than objectivity in the presence of complexity. Complex situations of the socio-scientific universe cause perturbations in the variables; there explaining complexity formed by the social embedding of variables. Indeed, human individuals, institutions and governments, and society at large are complex interrelated entities. Therefore, complex interrelations caused by social embedding remain submerged in social perturbations. However, interactions arising from social embedding also generate endogenous and complex relations. The contribution of this paper is in the area of endogenous learning in the wellbeing objective criterion function. The interrelationships between the emergent cognitive variables now cause interactive embedding, complexity, and social perturbations. Yet such perturbations are not altogether uncontrollable. They can be and need to be controlled for the purposes of social explanation—hence demanding predictability—even as the complex nature of evolutionary systemic learning proceeds. The controllability problem of extreme perturbations leads us to formalize a mathematical methodology to study controllable perturbations while avoiding extreme forms of perturbations in socio-scientific theory. (shrink)

Inception module is one of the most used variants in convolutional neural networks. It has a large portfolio of success cases in computer vision. In the past years, diverse inception flavours, differing in the number of branches, the size and the number of the kernels, have appeared in the scientific literature. They are proposed based on the expertise of the practitioners without any optimization process. In this work, an implementation of population-based incremental learning is proposed for automatic (...) class='Hi'>optimization of the hyperparameters of the inception module. This hyperparameters optimization undertakes classification of the MNIST database of handwritten digit images. This problem is widely used as a benchmark in classification, and therefore, the learned best configurations for the Inception module will be of wide use in the deep learning community. In order to reduce the carbon footprint of the optimization process, policies for reducing the redundant evaluations have been undertaken. As a consequence of this work, an evaluation of configurations of the inception module and a mechanism for optimizing hyperparameters in deep learning architectures are stated. (shrink)

Web services are self-describing and self-contained modular applications based on the network. With the deepening of web service applications, service consumers have gradually increased their requirements for service functions and service quality. Aiming at how to select the optimal plan from a large number of execution plans with the same function and different QoS characteristics, this paper proposes a web service selection algorithm that supports QoS global optimization and dynamic replanning. The algorithm uses position matrix coding to represent all (...) execution paths and replanning information of the service combination. By calculating the Hamming distance of the service quality between individuals, the quality of the service portfolio is improved. By specifying the total user time limit and implementing a good solution retention strategy, the problem of the impact of algorithm running time on service quality is solved. The experimental results show that the method proposed in this paper is effectively integrated into the development trend of QoS and close to the requester’s needs and can better meet user needs. This algorithm improves the user’s satisfaction with the returned service to a certain extent and improves the efficiency of service invocation. (shrink)

How are “interesting” research problems identified and made durable by academic researchers, particularly in situations defined by multiple evaluation principles? Building on two case studies of research groups working on rare diseases in academic biomedicine, we explore how group leaders arrange their groups to encompass research problems that latch onto distinct evaluation principles by dividing and combining work into “basic-oriented” and “clinical-oriented” spheres of inquiry. Following recent developments in the sociology of valuation comparing academics to capitalist entrepreneurs in pursuit of (...) varying kinds of worth, we argue that the metaphor of the portfolio is helpful in analyzing how group leaders manage these different research lines as “alternative investment options” from which they were variously hoping to capitalize. We argue portfolio development is a useful concept for exploring how group leaders fashion “entrepreneurial” practices to manage and exploit tensions between multiple matrices of valuation and conclude with suggestions for how this vocabulary can further extend analysis of epistemic capitalism within science and technology studies. (shrink)

This article analyzes investors’ portfolio selection problems in a two-period dynamic model of Knightian uncertainty. We account for the existence of portfolio inertia in this two-period framework. Furthermore, by incorporating investors’ updating behavior, we analyze how observing new information in the first period will affect investors’ behavior. By this analysis, we show that observing new information in the first period will expand portfolio inertia in the second period compared with the case in which observing new information has (...) not been gained in the first period if the degree of Knightian uncertainty is sufficiently large. (shrink)

This project seeks to highlight the benefits of the implementation and management of the teaching digital portfolio. In today's world full of technology and tools that facilitate daily activities, education and its various processes must also embrace the digital tools available and make them the basis for any innovation and improvement process. The teaching portfolio in physics has long been the means by which teachers have organized the processes, evidence, and other results of educational work. Nowadays, all that (...) range of evidence and productions, which signify the achievement and advances in each group of students, has been able to be integrated into technology. (shrink)

Les photos de ce portfolio ont été prises par Philippe Carta, Julien Goetz, Francis Guermann, Bernard Muscat et Michel Noirez. Projecteur et enrouleur 35 mm mobiles installés dans le vestibule de l’Opéra-Théâtre pour la projection de Moïse et Aaron – 24 mars 2011. Avant la projection de Moïse et Aaron, Jean-Marie Straub, debout face à l’écran de l’Opéra-Théâtre, vérifie la qualité de l’image et du son. François Narboni et Régine Palucci présentent Moïse et Aaron. A...

The relations between rationality and optimization have been widely discussed in the wake of Herbert Simon's work, with the common conclusion that the rationality concept does not imply the optimization principle. The paper is partly concerned with adding evidence for this view, but its main, more challenging objective is to question the converse implication from optimization to rationality, which is accepted even by bounded rationality theorists. We discuss three topics in succession: (1) rationally defensible cyclical choices, (2) (...) the revealed preference theory of optimization, and (3) the infinite regress of optimization. We conclude that (1) and (2) provide evidence only for the weak thesis that rationality does not imply optimization. But (3) is seen to deliver a significant argument for the strong thesis that optimization does not imply rationality. (shrink)

This paper examines the explanatory distinctness of wiring optimization models in neuroscience. Wiring optimization models aim to represent the organizational features of neural and brain systems as optimal (or near-optimal) solutions to wiring optimization problems. My claim is that that wiring optimization models provide design explanations. In particular, they support ideal interventions on the decision variables of the relevant design problem and assess the impact of such interventions on the viability of the target system.

Funding agencies and large public scientific institutions are increasingly using the term “research portfolio” as a means of characterizing their research. While portfolios have long been used as a heuristic for managing corporate R&D, they remain ill-defined in a science policy context where research is aimed at achieving societal outcomes. In this article we analyze the discursive uses of the term “research portfolio” and propose some general considerations for their application in science policy. We explore the use of (...) the term in private R&D and related scholarly literature in existing science policy practices, and seek insight in relevant literature in science policy scholarship. While the financial analogy can in some instances be instructive, a simple transposition from the world of finance or of corporate R&D to public research is problematic. However, we do identify potentially fruitful uses of portfolio analysis in science policy. In particular, our review suggests that the concept of research portfolio can indeed be a useful analytical instrument for tackling complex societal challenges. Specifically, the strands of scholarship identified suggest that the use of research portfolio should: i) recognize the diversity of research lines relevant for a given societal challenge, given the uncertainty and ambiguity of research outcomes; ii) examine the relationships between research options of a portfolio and the expected societal outcomes; and iii) adopt a systemic perspective to research portfolios – i.e. examine a portfolio as a functional whole, rather than as the sum of its parts. We argue that with these considerations, portfolio-driven approaches may foster social inclusion in science policy decisions, help deliberation between “alternative” portfolios to tackle complex societal challenges, as well as promote cost-effectiveness and transparency. (shrink)

Merging logic and mathematics in deductive inference-an innovative, cutting-edge approach. Optimization methods for logical inference? Absolutely, say Vijay Chandru and John Hooker, two major contributors to this rapidly expanding field. And even though "solving logical inference problems with optimization methods may seem a bit like eating sauerkraut with chopsticks... it is the mathematical structure of a problem that determines whether an optimization model can help solve it, not the context in which the problem occurs." Presenting powerful, proven (...) optimization techniques for logic inference problems, Chandru and Hooker show how optimization models can be used not only to solve problems in artificial intelligence and mathematical programming, but also have tremendous application in complex systems in general. They survey most of the recent research from the past decade in logic/optimization interfaces, incorporate some of their own results, and emphasize the types of logic most receptive to optimization methods-propositional logic, first order predicate logic, probabilistic and related logics, logics that combine evidence such as Dempster-Shafer theory, rule systems with confidence factors, and constraint logic programming systems. Requiring no background in logic and clearly explaining all topics from the ground up, Optimization Methods for Logical Inference is an invaluable guide for scientists and students in diverse fields, including operations research, computer science, artificial intelligence, decision support systems, and engineering. (shrink)

Mental representations have continuous as well as discrete, combinatorial properties. For example, while predominantly discrete, phonological representations also vary continuously; this is reflected by gradient effects in instrumental studies of speech production. Can an integrated theoretical framework address both aspects of structure? The framework we introduce here, Gradient Symbol Processing, characterizes the emergence of grammatical macrostructure from the Parallel Distributed Processing microstructure (McClelland, Rumelhart, & The PDP Research Group, 1986) of language processing. The mental representations that emerge, Distributed Symbol Systems, (...) have both combinatorial and gradient structure. They are processed through Subsymbolic Optimization–Quantization, in which an optimization process favoring representations that satisfy well-formedness constraints operates in parallel with a distributed quantization process favoring discrete symbolic structures. We apply a particular instantiation of this framework, λ-Diffusion Theory, to phonological production. Simulations of the resulting model suggest that Gradient Symbol Processing offers a way to unify accounts of grammatical competence with both discrete and continuous patterns in language performance. (shrink)

Mobile health applications that promise the user to help her with some aspect of her health are very popular: for-profit apps such as MyFitnessPal, Fitbit, or Headspace have tens of millions of users each. For-profit health apps are designed and run as optimization systems. One would expect that these health apps aim to optimize the health of the user, but in reality they aim to optimize user engagement and, in effect, conversion. This is problematic, I argue, because digital health (...) environments that aim to optimize user engagement risk being manipulative. To develop this argument, I first provide a brief analysis of the underlying business models and the resulting designs of the digital environments provided by popular for-profit health apps. In a second step, I present a concept of manipulation that can help analyze digital environments such as health apps. In the last part of the article, I use my concept of manipulation to analyze the manipulative potential of for-profit health apps. Although for-profit health can certainly empower their users, the conditions for empowerment also largely overlap with the conditions for manipulation. As a result, we should be cautious when embracing the empowerment discourse surrounding health apps. An additional aim of this article is to contribute to the rapidly growing literature on digital choice architectures and the ethics of influencing behavior through such choice architectures. I take health apps to be a paradigmatic example of digital choice architectures that give rise to ethical questions, so my analysis of the manipulative potential of health apps can also inform the larger literature on digital choice architectures. (shrink)

ABSTRACT. The relations between rationality and optimization have been widely discussed in the wake of Herbert Simon’s work, with the common conclusion that the rationality concept does not imply the optimization principle. The paper is partly concerned with adding evidence for this view, but its main, more challenging objective is to question the converse implication from optimization to rationality, which is accepted even by bounded rationality theorists. We discuss three topics in succession: (1) rationally defensible cyclical choices, (...) (2) the revealed preference theory of optimization, and (3) the infinite regress of optimization. We conclude that (1) and (2) provide evidence only for the weak thesis that rationality does not imply optimization. But (3) is seen to deliver a significant argument for the strong thesis that optimization does not imply rationality. (shrink)

This article presents a simple derivation of optimization models for reaction networks leading to a generalized form of the mass-action law, and compares the formal structure of Minimum Information Divergence, Quadratic Programming and Kirchhoff type network models. These optimization models are used in related articles to develop and illustrate the operation of ontology alignment algorithms and to discuss closely connected issues concerning the epistemological and statistical significance of sharp or precise hypotheses in empirical science.

The pandemic had serious implications for university education, specifically due to the transition from face-to-face teaching to online methodologies. This article analyzes the perception of students undergoing speech therapy from a Chilean University about the E-portfolio incorporation as an evaluative tool during the emergency virtual teaching due to the COVID-19 pandemic. From quantitative research, a survey of 38 questions based on Likert scales was applied to 108 penultimate year undergraduate students. The survey demonstrated that there is an improvement in (...) the methodology and teaching support, as well as in the creativity and professionalism of the students. (shrink)

Shareholders assume risk by investing. Sollars and Tuluca (2018) argue that while this does not justify a managerial policy of shareholder wealth maximization, it does justify compensating shareholders at the oftencalculated cost of equity—the cost that investors require given the level of risk they assume. Here, I show that this can be unfair if the cost of equity is unfair. I then show how shareholder wealth maximization as a managerial imperative is better justified on other grounds.

We reopen the investigation into the formal and conceptual relationship between bidirectional optimality theory (Blutner in J Semant 15(2):115–162, 1998 , J Semant 17(3):189–216, 2000 ) and game theory. Unlike a likeminded previous endeavor by Dekker and van Rooij (J Semant 17:217–242, 2000 ), we consider signaling games not strategic games, and seek to ground bidirectional optimization once in a model of rational step-by-step reasoning and once in a model of reinforcement learning. We give sufficient conditions for equivalence of (...) bidirectional optimality and the former, and show based on numerical simulations that bidirectional optimization may be thought of as a process of reinforcement learning with lateral inhibition. (shrink)

Optimization models treat natural selection as a process tending to produce maximal adaptedness to the environment, measured on some "criterion scale" defining the optimal phenotype. These models are descriptively adequate if they describe the outcomes of evolutionary processes. They are dynamically adequate if the variables which describe the outcomes also are responsible for those evolutionary outcomes. Optimality models can be descriptively adequate, but dynamically unrealistic. Relying on cases from evolutionary ecology, I provide reasons to question the dynamic adequacy of (...) optimality models, and offer reasons for distinguishing, at least at a theoretical level, between satisficing and optimizing. (shrink)

David Marr's theory of vision has been a rich source of inspiration, fascination and confusion. I will suggest that some of this confusion can be traced to discrepancies between the way Marr developed his theory in practice and the way he suggested such a theory ought to be developed in his explicit metatheoretical remarks. I will address claims that Marr's theory may be seen as an optimizing theory, along with the attendant suggestion that optimizing assumptions may be inappropriate for cognitive (...) mechanisms just as anti-adaptationists have argued they are inappropriate for other physiological mechanisms. I will discuss the nature of optimizing assumptions and theories. Considering various difficulties in identifying and assessing optimizing assumptions, I will suggest that Marr's theory is not purely an optimizing theory and that reaction to Marr on this issue prompts interesting considerations for the development of inter-disciplinary constraints in the cognitive and brain sciences. (shrink)

In this paper the Centering model of anaphoraresolution and discourse coherence(Grosz et al. 1983, 1995)is reformulated in terms of Optimality Theory (OT)(Prince and Smolensky 1993). One version of the reformulated modelis proven to be descriptively equivalent to an earlier algorithmicstatement of Centering due to Brennan, Friedman and Pollard(1987). However, the new model is stated declaratively, and makesclearer the status of the various constraints used in the theory. Inthe second part of the paper, the model is extended, demonstratingthe advantages of the (...) OT reformulation, and capturing formallyideas originally described by Grosz, Joshi and Weinstein. Three newapplications of the extended OT Centering model are described:generation of linguistic forms from meanings, the evaluation andoptimization of extended texts, and the interpretation of accentedpronouns. (shrink)

Although clinical ethics consultation is a high-stakes endeavor with an increasing prominence in health care systems, progress in developing standards for quality is challenging. In this article, we describe the results of a pilot project utilizing portfolios as an evaluation tool. We found that this approach is feasible and resulted in a reasonably wide distribution of scores among the 23 submitted portfolios that we evaluated. We discuss limitations and implications of these results, and suggest that this is a significant step (...) on the pathway to an eventual certification process for clinical ethics consultants. (shrink)

This article argues that evolutionary models based on selection validate, under appropriate conditions, the relevance of optimality as an explanatory mechanism in rational choice theory. The reason is that these frameworks share the mechanism that drives the results, namely, optimization, even if they situate it at different levels. The consequences of our argument are twofold. First, it resolves the tension between those predictions of rational choice theory that are accurate and the evidence showing that individuals seldom optimize. Second, it (...) relativizes the explanatory import of rationality without diminishing the role of optimization as a mechanism. (shrink)

Visual cryptography is a cryptographic technique that allows visual information to be encrypted so that the human optical system can perform the decryption without any cryptographic computation. The halftone visual cryptography scheme (HVCS) is a type of visual cryptography (VC) that encodes the secret image into halftone images to produce secure and meaningful shares. However, the HVC scheme has many unsolved problems, such as pixel expansion, low contrast, cross-interference problem, and difficulty in managing share images. This article aims to enhance (...) the visual quality and avoid the problems of cross-interference and pixel expansion of the share images. It introduces a novel optimization of color halftone visual cryptography (OCHVC) scheme by using two proposed techniques: hash codebook and construction techniques. The new techniques distribute the information pixels of a secret image into a halftone cover image randomly based on a bat optimization algorithm. The results show that these techniques have enhanced security levels and make the proposed OCHVC scheme more robust against different attacks. The OCHVC scheme achieves mean squared error (MSE) of 95.0%, peak signal-to-noise ratio (PSNR) of 28.3%, normalized cross correlation (NCC) of 99.4%, and universal quality index (UQI) of 99.3% on average for the six shares. Subsequently, the experiment results based on image quality metrics show improvement in size, visual quality, and security for retrieved secret images and meaningful share images of the OCHVC scheme. Comparing the proposed OCHVC with some related works shows that the OCHVC scheme is more effective and secure. (shrink)

We analyze the comparative static effects of changes in the means, the standard deviations and the covariance of asset returns in a standard portfolio selection problem when investors have mean variance preferences. Simple and intuitive characterizations in terms of the elasticity of risk aversion are provided.

Optimization for vertical vibration performance of a rail-train coupling system is investigated in this paper with the introduction of inerters for both primary and secondary suspensions. A model of a typical Chinese passenger train that travels on a traditional rail with track, sleepers, and ballast is simulated. The goal is to improve the ride quality for the train and vibration attenuation for the rail system in response to track irregularities. Optimizations for only inertance and all suspension parameters are carried (...) out by the particle swarm algorithm. Performance benefits for both the train and the rail system are demonstrated and suspension layouts with inerters connected in parallel and series are compared with the traditional one in both time domain and frequency domain. (shrink)

The Genetic Algorithm (GA) and Simulated Annealing (SA), two techniques for global optimization, were applied to a reduced (simplified) form of the phase problem (RPP) in computational crystallography. Results were compared with those of "enhanced pair flipping" (EPF), a more elaborate problem-specific algorithm incorporating local and global searches. Not surprisingly, EPF did better than the GA or SA approaches, but the existence of GA and SA techniques more advanced than those used in this study suggest that these techniques still (...) hold promise for phase problem applications. The RPP is, furthermore, an excellent test problem for such global optimization methods. (shrink)

Building on a base of simple economic theory and elementary linear algebra and calculus, this broad treatment of static and dynamic optimization methods discusses the importance of shadow prices and functions defined by solutions of optimization problems.

The teaching management department carries all the work related to teaching in the whole school. A scientific, efficient, and complete teaching management system cannot only help the teaching management department improve work efficiency and quality but also greatly reduce many problems caused by manual labour risk. This paper designs and implements a teaching management system based on an improved association rule algorithm. First, aiming at the low efficiency of the Apriori algorithm for mining association rules, an association rule model based (...) on interest is proposed. Second, use the MapReduce calculation model to partition the transaction database, then use the improved Apriori optimization algorithm for mining, and finally merge the mining results to obtain frequent itemsets. Through experiments, the optimized algorithm has greatly improved selection mining and computing time than traditional algorithms. (shrink)

Traditional portfolio selection models mainly obtain the optimized portfolio ratio by focusing on the prices of financial products. However, investors’ multiple preferences and risk appetites are also significant factors that should be taken into account. In consideration of these two factors simultaneously, we propose a double-hierarchy model in this paper. Specifically, the first hierarchy quantifies investors’ risk appetite based on a historical simulation method and probabilistic preference theory. This hierarchy can be utilized to describe investors’ variable risk appetites (...) and ensure the obtained investment ratios meet investors’ immediate risk requirements. Then, using the cross-efficiency evaluation principle, the optimal investment ratios can be derived by fusing investors’ multiple preferences and risk appetites in the second hierarchy. Lastly, an illustrative example about evaluating the 10 largest capitalized stocks on the Shenzhen Stock Exchange is given to verify the feasibility and effectiveness of our newly proposed model. We make the theoretical contribution to improve the traditional portfolio selection model, especially considering investors’ subjective preferences and risk appetite. Moreover, the proposed model can be practical for assisting investors with their investment strategies in real life. (shrink)