An interactive decision support system for an aggregate production planning model based on multiple criteria mixed integer linear programming

In this paper, we present an aggregate production planning (APP) model applied to a Portuguese firm that produces construction materials. A multiple criteria mixed integer linear programming (MCMILP) model is developed with the following performance criteria: (1) maximize profit, (2) minimize late orders, and (3) minimize work force level changes. It includes certain operational features such as partial inflexibility of the work force, legal restrictions on workload, work force size (workers to be hired and downsized), workers in training, and production and inventory capacity. The purpose is to determine the number of workers for each worker type, the number of overtime hours, the inventory level for each product category, and the level of subcontracting in order to meet the forecasted demand for a planning period of 12 months. Additionally, a decision support system (DSS) based on the MCMILP model is proposed. It will help practitioners find the “best” solution for an APP problem without having to familiarize themselves with the mathematical complexities associated with the model. An example to illustrate the use of the DSS is also included.     

Will evolutionary psychology become extinct? Evolutionary psychology as the Leaning Tower of Pisa

ABSTRACT

Evolutionary psychology has as its foundation the classical Darwinian-Wallace theory of evolution. Using this theory as a guideline, evolutionary psychologists have interpreted human behaviors from an adaptationist outlook using a circular logic wherein no matter what the behavior is being looked at it is always given an evolutionary rationale. Additionally, there is much speculation as to evolutionary effects in the past and these speculations are seen as factual. Furthermore, there is evidence that the classical theory is flawed in that the emphasis on adaptation as the basis for evolution is incorrect. In that there is no actual evidence that Natural Selection (i.e., adaptation) has led to speciation. Previous scientists who have criticized the classical theory are cited, who made the case for speciation having occurred through a sudden “saltationist” process rather than the classical gradual process. As such, the author predicts that evolutionary psychology may ultimately become extinct as a subdiscipline.     

The beta exponentiated Weibull distribution

The Weibull distribution is one of the most important distributions in reliability. For the first time, we introduce the beta exponentiated Weibull distribution which extends recent models by Lee et al. [Beta-Weibull distribution: some properties and applications to censored data, J. Mod. Appl. Statist. Meth. 6 (2007), pp. 173–186] and Barreto-Souza et al. [The beta generalized exponential distribution, J. Statist. Comput. Simul. 80 (2010), pp. 159–172]. The new distribution is an important competitive model to the Weibull, exponentiated exponential, exponentiated Weibull, beta exponential and beta Weibull distributions since it contains all these models as special cases. We demonstrate that the density of the new distribution can be expressed as a linear combination of Weibull densities. We provide the moments and two closed-form expressions for the moment-generating function. Explicit expressions are derived for the mean deviations, Bonferroni and Lorenz curves, reliability and entropies. The density of the order statistics can also be expressed as a linear combination of Weibull densities. We obtain the moments of the order statistics. The expected information matrix is derived. We define a log-beta exponentiated Weibull regression model to analyse censored data. The estimation of the parameters is approached by the method of maximum likelihood. The usefulness of the new distribution to analyse positive data is illustrated in two real data sets.     

Adaptive PORT–MVRB estimation: an empirical comparison of two heuristic algorithms

In this article, we deal with an empirical comparison of two data-driven heuristic procedures of estimation of a positive extreme value index (EVI), working thus with heavy right tails. The semi-parametric EVI-estimators under consideration, the so-called peaks over random threshold (PORT)–minimum-variance reduced-bias (MVRB) EVI-estimators, are location and scale-invariant estimators, based on the PORT methodology applied to second-order MVRB EVI-estimators. Trivial adaptations of these algorithms make them work for a similar estimation of other parameters of extreme events, such as the Value-at-Risk at a level p, the expected shortfall and the probability of exceedance of a high level x, among others. Applications to simulated data sets and to real data sets in the field of finance are provided.     

Bias reduction of a tail index estimator through an external estimation of the second-order parameter

In this paper, we first consider a class of consistent semi-parametric estimators of a positive tail index γ, parameterised in a tuning or control parameter α. Such a control parameter enables us to have access, for any available sample, to an estimator of the tail index γ with a null dominant component of asymptotic bias, and consequently with a reasonably flat mean squared error pattern, as a function of k, the number of top-order statistics considered. Such a control parameter depends on a second-order parameter ρ, which will be adequately estimated so that we may achieve a high efficiency relative to the classical Hill estimator, provided we use a number of top-order statistics larger than the one usually required for the estimation through the Hill estimator. An illustration of the behaviour of the estimators is provided, through the analysis of the daily log-returns on the Euro–US$ exchange rates.     

Are vascular epiphytes in urban green areas subject to the homogenization of biodiversity? A case study in the Brazilian Atlantic Forest

Urbanization is a disturbance process that can select species and result in biodiversity homogenization. Despite this, urban green areas shelter nature and are also important to human welfare. Epiphytes are an important functional group present in such areas, that are rarely studied. We evaluated the vascular epiphytic component in 26 urban green areas in the Brazilian Atlantic Forest and tested hypotheses related to the anthropogenic disturbances: 1) the community of epiphytes in urban green areas presents low richness and diversity of species; 2) there is low beta diversity due to flora homogenization represented by a reduced set of more tolerant species to disturbance. A total of 2288 trees (1563 representing phorophytes) and 110 epiphytic species were sampled. Six species were dominant, resulting in low diversity values, but some green areas had relatively high richness. The similarity found between the majority of the sampled areas suggests that epiphytic flora is subject to homogenization due to environmental filters. We found a high richness of species without adaptations to the epiphytic lifeform (accidental epiphytes) (42% of total sampled). Some results suggest that more comprehensive ecological and/or floristic studies about the epiphytes in the urban environment are necessary, such as Orchidaceae as the second richest family (since it is often poor in urban areas). More information about the species distribution patterns are necessary, both regarding the anthropized environments and the relationships with exotic or native phorophytes, as well as to enhance the knowledge of the ecological functions played by the epiphytes in these places.

     

Statistical choice of extreme value domains of attraction — a comparative analysis

In recent years there has been a significant development of several procedures to infer about the extremal model that most conveniently describes the distribution function of the underlying population from a data set. The problem of choosing one of the three extremal types, giving preference to the Gumbel model for the null hypothesis, has frequently received the general designation of statistical choice of extremal models and has been handled under different set-ups by numerous authors. Recently, a test procedure, referred by Hasofer and Wang (1992), gave place to a comparison with some of other connected perspectives. Such a topic, jointly with some suggestions for applicability to real data, is the theme of the present paper.     

The Exponentiated G Poisson Model

We study a new family of distributions defined by the minimum of the Poisson random number of independent identically distributed random variables having a general exponentiated G distribution. Some mathematical properties of the new family including ordinary and incomplete moments, quantile and generating functions, mean deviations, order statistics and their moments, reliability, and Shannon entropy are derived. Maximum likelihood estimation of the model parameters is investigated. Two special models of the new family are discussed. We perform an application to a real data set to show the potentiality of the proposed family.