Single-objective spreading algorithm

This paper addresses the problem of finding several different solutions with the same optimum performance in single objective real-world engineering problems. In this paper a parallel robot design is proposed. Thereby, this paper presents a genetic algorithm to optimize uni-objective problems with an infinite number of optimal solutions. The algorithm uses the maximin concept and ε-dominance to promote diversity over the admissible space. The performance of the proposed algorithm is analyzed with three well-known test functions and a function obtained from practical real-world engineering optimization problems. A spreading analysis is performed showing that the solutions drawn by the algorithm are well dispersed.

Environmental management problems, future generations and social decisions

The decisions of many individuals and social groups, taking according to well-defined objectives, are causing serious social and environmental problems, in spite of following the dictates of economic rationality. There are many examples of serious problems for which there are not yet appropriate solutions, such as management of scarce natural resources including aquifer water or the distribution of space among incompatible uses. In order to solve these problems, the paper first characterizes the resources and goods involved from an economic perspective. Then, for each case, the paper notes that there is a serious divergence between individual and collective interests and, where possible, it designs the procedure for solving the conflict of interests. With this procedure, the real opportunities for the application of economic theory are shown, and especially the theory on collective goods and externalities. The limitations of conventional economic analysis are shown and the opportunity to correct the shortfalls is examined. Many environmental problems, such as climate change, have an impact on different generations that do not participate in present decisions. The paper shows that for these cases, the solutions suggested by economic theory are not valid. Furthermore, conventional methods of economic valuation (which usually help decision-makers) are unable to account for the existence of different generations and tend to obviate long-term impacts. The paper analyzes how economic valuation methods could account for the costs and benefits enjoyed by present and future generations. The paper studies an appropriate consideration of preferences for future consumption and the incorporation of sustainability as a requirement in social decisions, which implies not only more efficiency but also a fairer distribution between generations than the one implied by conventional economic analysis.

Sairaanhoitajaopiskelijoiden ohjattujen käytännön harjoittelujen aikana ilmenneet eettiset ongelmat

Ethical problems occurring during the practical training period of Finnish nursing students The present study focused on nursing students adopting the professional code of conduct during their supervised practical training. The study was carried out in two phases. During the first phase, the objective was to survey ethical problems occurring in practical training as well as how these problems are detected and resolved by nursing students and their supervisors at different stages of their studies. In the second phase, the capability of the nursing students about to graduate to detect and resolve ethical problems was described and analyzed. The students’ capacity for self-instruction, independent search for information as well as factors related to teaching of ethics were determined within this phase. Further, an extensive literature review was carried out to complement the study. Thus, the main objective of the thesis was to make suggestions for the development of the teaching of ethics and supervision in nursing studies and in practice. In the first part of the empirical phase (2002–2005), the views of the nursing students (n =18) were clarified with themed open essay questions. Furthermore, the views of the supervising nurses (n = 115) were established by utilizing a series of themed questions and group interviews. During the second phase (2006–2007), the data for the analyses were collected from nursing students in their graduating stage (n = 319) by a national Internet-based questionnaire. The results of the first phase were examined with contentanalysis and those of the second phase both statistically and by using content analysis. Ethical problems occurring during supervised practical training were typically connected to a patient or a client, a member of the nursing staff or to a student, while solutions were connected to preparation and the action to solve the problem in question. Ethical dilemmas were classified as legal, ethical comportment and uncertainty problems as well as personal and institutional ones. The solutions for these problems were further grouped as based on facts, instructor/staff/member/specialist or patient/client/relative. The results showed that although the nursing students about to graduate had detected many ethical problems both independently as well as together with the nursing staff during every practical training period, they were able to resolve only few of them. Ethical problems were most frequently encountered during training in psychiatric nursing. On the grounds of their own impressions, the nursing students stated that their ability to detect and solve ethical problems improved during their training period. The primary factors related to this enhancement of their skills were teaching and the students’ readiness for selfinstruction. Gender, orientation of the studies and age were observed to be the most important among the underlying factors influencing the capability to detect and solve ethical problems as well as to engage in self-instruction. Based on the results obtained, suggestions for development as well as topics for further studies are presented through teaching of professional ethics and supervision during practical training.

Zero-sum problems in finite cyclic groups

The purpose of this thesis is to investigate some open problems in the area of combinatorial number theory referred to as zero-sum theory. A zero-sequence in a finite cyclic group G is said to have the basic property if it is equivalent under group automorphism to one which has sum precisely IGI when this sum is viewed as an integer. This thesis investigates two major problems, the first of which is referred to as the basic pair problem. This problem seeks to determine conditions for which every zero-sequence of a given length in a finite abelian group has the basic property. We resolve an open problem regarding basic pairs in cyclic groups by demonstrating that every sequence of length four in Zp has the basic property, and we conjecture on the complete solution of this problem. The second problem is a 1988 conjecture of Kleitman and Lemke, part of which claims that every sequence of length n in Zn has a subsequence with the basic property. If one considers the special case where n is an odd integer we believe this conjecture to hold true. We verify this is the case for all prime integers less than 40, and all odd integers less than 26. In addition, we resolve the Kleitman-Lemke conjecture for general n in the negative. That is, we demonstrate a sequence in any finite abelian group isomorphic to Z2p (for p ~ 11 a prime) containing no subsequence with the basic property. These results, as well as the results found along the way, contribute to many other problems in zero-sum theory.

Tactical Vehicle Routing Planning with Application to Milk Collection and Distribution

De nombreux problèmes pratiques qui se posent dans dans le domaine de la logistique, peuvent être modélisés comme des problèmes de tournées de véhicules. De façon générale, cette famille de problèmes implique la conception de routes, débutant et se terminant à un dépôt, qui sont utilisées pour distribuer des biens à un nombre de clients géographiquement dispersé dans un contexte où les coûts associés aux routes sont minimisés. Selon le type de problème, un ou plusieurs dépôts peuvent-être présents. Les problèmes de tournées de véhicules sont parmi les problèmes combinatoires les plus difficiles à résoudre. Dans cette thèse, nous étudions un problème d’optimisation combinatoire, appartenant aux classes des problèmes de tournées de véhicules, qui est liée au contexte des réseaux de transport. Nous introduisons un nouveau problème qui est principalement inspiré des activités de collecte de lait des fermes de production, et de la redistribution du produit collecté aux usines de transformation, pour la province de Québec. Deux variantes de ce problème sont considérées. La première, vise la conception d’un plan tactique de routage pour le problème de la collecte-redistribution de lait sur un horizon donné, en supposant que le niveau de la production au cours de l’horizon est fixé. La deuxième variante, vise à fournir un plan plus précis en tenant compte de la variation potentielle de niveau de production pouvant survenir au cours de l’horizon considéré. Dans la première partie de cette thèse, nous décrivons un algorithme exact pour la première variante du problème qui se caractérise par la présence de fenêtres de temps, plusieurs dépôts, et une flotte hétérogène de véhicules, et dont l’objectif est de minimiser le coût de routage. À cette fin, le problème est modélisé comme un problème multi-attributs de tournées de véhicules. L’algorithme exact est basé sur la génération de colonnes impliquant un algorithme de plus court chemin élémentaire avec contraintes de ressources. Dans la deuxième partie, nous concevons un algorithme exact pour résoudre la deuxième variante du problème. À cette fin, le problème est modélisé comme un problème de tournées de véhicules multi-périodes prenant en compte explicitement les variations potentielles du niveau de production sur un horizon donné. De nouvelles stratégies sont proposées pour résoudre le problème de plus court chemin élémentaire avec contraintes de ressources, impliquant dans ce cas une structure particulière étant donné la caractéristique multi-périodes du problème général. Pour résoudre des instances de taille réaliste dans des temps de calcul raisonnables, une approche de résolution de nature heuristique est requise. La troisième partie propose un algorithme de recherche adaptative à grands voisinages où de nombreuses nouvelles stratégies d’exploration et d’exploitation sont proposées pour améliorer la performances de l’algorithme proposé en termes de la qualité de la solution obtenue et du temps de calcul nécessaire.

A knowledge-based evolution strategy for the multi-objective minimum spanning tree problem

A fast Knowledge-based Evolution Strategy, KES, for the multi-objective minimum spanning tree, is presented. The proposed algorithm is validated, for the bi-objective case, with an exhaustive search for small problems (4-10 nodes), and compared with a deterministic algorithm, EPDA and NSGA-II for larger problems (up to 100 nodes) using benchmark hard instances. Experimental results show that KES finds the true Pareto fronts for small instances of the problem and calculates good approximation Pareto sets for larger instances tested. It is shown that the fronts calculated by YES are superior to NSGA-II fronts and almost as good as those established by EPDA. KES is designed to be scalable to multi-objective problems and fast due to its small complexity.

Cytotype-specific ISSR profiles and karyotypes in the Neotropical genus Eigenmannia (Teleostei: Gymnotiformes)

The genus Eigenmannia (Teleostei: Gymnotiformes), a widely distributed fish genus from the Neotropical region, presents very complex morphological patterns and many taxonomic problems. It is suggested that this genus harbors a species complex that is hard to differentiate using only morphological characteristics. As a result, many species of Eigenmannia may be currently gathered under a common name. With the objective of providing new tools for species characterization in this group, an analysis of the polymorphism of DNA inter-simple sequence repeats (ISSR), obtained by single primer amplification reaction (SPAR), combined with karyotype identification, was carried out in specimens sampled from populations of the Upper Parana, So Francisco and Amazon river basins (Brazil). Specific ISSR patterns generated by primers (AAGC)(4) and (GGAC)(4) were found to characterize the ten cytotypes analyzed, even though the cytotypes 2n = 38 and 2n = 38 XX:XY, from the Upper Parana basin, share some ISSR amplification patterns. The geographical distribution of all Eigenmannia specimens sampled was inferred, showing the cytotype 2n = 31/2n = 32 as the most frequent and largely distributed in the Upper Parana basin. The cytotype 2n = 34 was reported for the first time in the genus Eigenmania, restricted to the So Francisco basin. Polymorphic ISSR patterns were also detected for each cytotype. Considering our results and the data reported previously in the literature, it is suggested that many of the forms of Eigenmannia herein analyzed might be regarded as different species. This work reinforces the importance of employing diverse approaches, such as molecular and cytogenetic characterization, to address taxonomic and evolutionary issues.

A Diagnostic Assessment Of Evolutionary Multiobjective Optimization For Water Resources Systems

This study contributes a rigorous diagnostic assessment of state-of-the-art multiobjective evolutionary algorithms (MOEAs) and highlights key advances that the water resources field can exploit to better discover the critical tradeoffs constraining our systems. This study provides the most comprehensive diagnostic assessment of MOEAs for water resources to date, exploiting more than 100,000 MOEA runs and trillions of design evaluations. The diagnostic assessment measures the effectiveness, efficiency, reliability, and controllability of ten benchmark MOEAs for a representative suite of water resources applications addressing rainfall-runoff calibration, long-term groundwater monitoring (LTM), and risk-based water supply portfolio planning. The suite of problems encompasses a range of challenging problem properties including (1) many-objective formulations with 4 or more objectives, (2) multi-modality (or false optima), (3) nonlinearity, (4) discreteness, (5) severe constraints, (6) stochastic objectives, and (7) non-separability (also called epistasis). The applications are representative of the dominant problem classes that have shaped the history of MOEAs in water resources and that will be dominant foci in the future. Recommendations are provided for which modern MOEAs should serve as tools and benchmarks in the future water resources literature.

Estudo experimental de microrreservatórios para controle do escoamento superficial

O crescimento desordenado das cidades tem gerado muitos problemas de infraestrutura e impactos ao meio ambiente. No que se refere aos recursos hídricos, problemas de abastecimento, poluição e enchentes são cada vez mais constantes. À medida que a cidade se urbaniza e se impermeabiliza, vários são os impactos que vão atuar no sentido de provocar ou agravar as enchentes urbanas. No caso da drenagem urbana é preciso repensar o que vem sendo feito, buscando soluções alternativas às atualmente apresentadas, uma vez que estas não têm se mostrado eficientes. Uma possível solução para estes problemas é a aplicação de medidas de controle do escoamento na fonte, dentre elas o microrreservatório de detenção. Baseando-se na busca de soluções para os problemas citados, este trabalho tem o objetivo geral de verificar experimentalmente o funcionamento de microrreservatórios de detenção no controle da geração do escoamento superficial. Para isso foi construído um módulo experimental nas dependências do IPH, composto por um microrreservatório de 1m3, monitorado através de linígrafos que registram as vazões de entrada e saída, recebendo contribuição de uma área de 337,5m2. O período de monitoramento iniciou em agosto de 2000 e se estendeu até janeiro de 2001. De posse dos dados coletados foi possível fazer uma análise da eficiência deste dispositivo no controle do escoamento superficial, bem como estudar a real necessidade de manutenção da estrutura. Também foi feita uma análise do impacto da presença de sedimentos (folhagens) na água de escoamento nas estruturas de descarga. O trabalho também deixa uma contribuição no que se refere a critérios de projeto e dimensionamento de estruturas desta natureza. Finalmente foi possível concluir que o sistema é eficiente no controle da vazão de pico, porém o reservatório não permitiu um aumento no tempo de resposta da bacia.

Lagrangian heuristic for a class of the generalized assignment problems

A Lagrangian based heuristic is proposed for many-to-many assignment problems taking into account capacity limits for task and agents. A modified Lagrangian bound studied earlier by the authors is presented and a greedy heuristic is then applied to get a feasible Lagrangian-based solution. The latter is also used to speed up the subgradient scheme to solve the modified Lagrangian dual problem. A numerical study is presented to demonstrate the efficiency of the proposed approach. (C) 2010 Elsevier Ltd. All rights reserved.

Sustainable development: changing production patterns, social equity and the environment

Includes bibliography

Expenditures, investment and financing for sustainable development in Brazil

Includes bibliography

Multi-choice mixed integer goal programming optimization for real problems in a sugar and ethanol milling company

Goal Programming (GP) is an important analytical approach devised to solve many realworld problems. The first GP model is known as Weighted Goal Programming (WGP). However, Multi-Choice Aspirations Level (MCAL) problems cannot be solved by current GP techniques. In this paper, we propose a Multi-Choice Mixed Integer Goal Programming model (MCMI-GP) for the aggregate production planning of a Brazilian sugar and ethanol milling company. The MC-MIGP model was based on traditional selection and process methods for the design of lots, representing the production system of sugar, alcohol, molasses and derivatives. The research covers decisions on the agricultural and cutting stages, sugarcane loading and transportation by suppliers and, especially, energy cogeneration decisions; that is, the choice of production process, including storage stages and distribution. The MCMIGP allows decision-makers to set multiple aspiration levels for their problems in which the more/higher, the better and the less/lower, the better in the aspiration levels are addressed. An application of the proposed model for real problems in a Brazilian sugar and ethanol mill was conducted; producing interesting results that are herein reported and commented upon. Also, it was made a comparison between MCMI GP and WGP models using these real cases. © 2013 Elsevier Inc.

Automatic design of Ant Colony Optimization for permutation problems

In this study, we present a framework based on ant colony optimization (ACO) for tackling combinatorial problems. ACO algorithms have been applied to many diferent problems, focusing on algorithmic variants that obtain high-quality solutions. Usually, the implementations are re-done for various problem even if they maintain the same details of the ACO algorithm. However, our goal is to generate a sustainable framework for applications on permutation problems. We concentrate on understanding the behavior of pheromone trails and specific methods that can be combined. Eventually, we will propose an automatic offline configuration tool to build an efective algorithm. ---RESUMEN---En este trabajo vamos a presentar un framework basado en la familia de algoritmos ant colony optimization (ACO), los cuales están dise~nados para enfrentarse a problemas combinacionales. Los algoritmos ACO han sido aplicados a diversos problemas, centrándose los investigadores en diversas variantes que obtienen buenas soluciones. Normalmente, las implementaciones se tienen que rehacer, inclusos si se mantienen los mismos detalles para los algoritmos ACO. Sin embargo, nuestro objetivo es generar un framework sostenible para aplicaciones sobre problemas de permutaciones. Nos centraremos en comprender el comportamiento de la sendas de feromonas y ciertos métodos con los que pueden ser combinados. Finalmente, propondremos una herramienta para la configuraron automática offline para construir algoritmos eficientes.

Interval-based ranking in noisy evolutionary multiobjective optimization

As one of the most competitive approaches to multi-objective optimization, evolutionary algorithms have been shown to obtain very good results for many realworld multi-objective problems. One of the issues that can affect the performance of these algorithms is the uncertainty in the quality of the solutions which is usually represented with the noise in the objective values. Therefore, handling noisy objectives in evolutionary multi-objective optimization algorithms becomes very important and is gaining more attention in recent years. In this paper we present ?-degree Pareto dominance relation for ordering the solutions in multi-objective optimization when the values of the objective functions are given as intervals. Based on this dominance relation, we propose an adaptation of the non-dominated sorting algorithm for ranking the solutions. This ranking method is then used in a standardmulti-objective evolutionary algorithm and a recently proposed novel multi-objective estimation of distribution algorithm based on joint variable-objective probabilistic modeling, and applied to a set of multi-objective problems with different levels of independent noise. The experimental results show that the use of the proposed method for solution ranking allows to approximate Pareto sets which are considerably better than those obtained when using the dominance probability-based ranking method, which is one of the main methods for noise handling in multi-objective optimization.