O presente trabalho explora como duas abordagens gerais da complexidade - ciências da complexidade e pensamento complexo - estão influenciando e podem vir a influenciar a gestão de sistemas organizacionais produtivos. Constata-se um aumento de publicações que relacionam a Complexidade à Gestão. Por meio de análise de conteúdo de trabalhos acadêmicos internacionais e nacionais identifica-se uma diminuição na ênfase inicial sobre teoria do caos e fractais e uma tendência recente na exploração da dinâmica de redes, ao mesmo tempo em que modelos baseados em agentes são cada vez mais explorados (associados à idéia de sistemas adaptativos complexos - SAC). Na produção nacional nota-se também a presença de idéias de cunho mais filosófico relacionadas à complexidade, notoriamente as do pensamento complexo do francês Edgar Morin. Com base na história do pensamento científico são identificados fundamentos do paradigma mecanicista dominante e fatores que estão contribuindo para transição de fase desse paradigma, relacionados ao aumento de complexidade na ciência e ao surgimento das ciências da complexidade. Estas ciências são caracterizadas como um processo evolutivo da Teoria Geral de Sistemas e possuem uma diversidade de contribuições em evolução, as quais têm sido utilizadas como referência para teorias e modelos de gestão de sistemas organizacionais produtivos. Explora-se a importância do desenvolvimento de um pensamento \'mais\' complexo e sua relação com a gestão. Apresenta-se uma discussão crítica sobre o uso de conceitos relacionados à complexidade, ressaltando-se que não existe um modelo de uma \'Teoria Geral da Complexidade\'. Avalia-se como esses conceitos são e podem vir a ser aplicados na Engenharia de Produção, por meio de: estudo de caso sobre o desenvolvimento e implementação de um sistema auto-organizado de solução de problemas em uma empresa de Agrobusiness; análise crítica, sob a ótica da complexidade, de trabalhos da área; e apresentação de propostas teóricas para aplicação do pensamento complexo. Conclui-se que as perspectivas da complexidade estão diretamente relacionadas a uma mudança de paradigma - na abrangência de um supra-paradigma, nos moldes de Kuhn - que passou do seu ponto de retorno, e que tais perspectivas afetarão cada vez mais a gestão de sistemas produtivos. / The present work explores how two general approaches of complexity - complexity sciences and complex thought - are influencing and may come to influence productive organizational systems management. An increase in publications relating Complexity to Management can be observed. By analyzing the content of international and Brazilian academic works, a decrease in the initial emphasis on the chaos theory and fractals is identified as well as a recent trend in the exploration of networks dynamics, at the same time at which models based on agents are more and more explored (associated to the idea of complex adaptative systems - CAS). In the Brazilian production, also noticed is the presence of ideas of a more philosophical characteristic related to complexity, notoriously those of complex thought by the French Edgar Morin. Based on the history of scientific thought, foundations of the dominant mechanicist paradigm are identified as well as factors that are contributing to this paradigm phase transition, concerning the increase in complexity in science and to the emergence of complexity sciences. These sciences are characterized as an evolutive process of the General Theory of Systems and count on a wide range of contributions in evolution, which have been used as a reference for theories and models of productive organizational systems management. The importance of the development of a \'more\' complex thought and its relationship with management are explored. A critical discussion is presented on the use of concepts related to complexity, pointing out that there is not a model for a \'General Theory of Complexity\'. How these concepts are and may come to be applied in Production Engineering is evaluated, by means of: case study on the development and implementation of a problem-solving self-organized system in an Agribusiness company; critical analysis, under the complexity view, of works in the area; and presentation of theoretical proposals for applying complex thought. It is concluded that the perspectives of complexity are directly related to a change in paradigm - in the comprehensiveness of a supra-paradigm, following Kuhn\'s models - which went beyond its turning point, and that these perspectives will more and more affect productive systems management.

Orientador: Marcus Aloízio Martinez de Aguiar / Tese (doutorado) - Universidade Estadual de Campinas, Instituto de Física Gleb Wataghin / Made available in DSpace on 2018-08-17T22:18:58Z (GMT). No. of bitstreams: 1 Hisi_AndreiaNaluSoares_D.pdf: 5934176 bytes, checksum: da28bbee37b83ef238c0e0210999475e (MD5) Previous issue date: 2011 / Resumo: Todos os organismos vivos interagem com indivíduos de sua e de outras espécies, formando uma rede complexa de interações que tem um papel importante na preservação da biodiversidade. Entender o comportamento subjacente e a estabilidade destes sistemas é de fundamental importância na conservação destes recursos. Neste trabalho estudamos uma rede com apenas quatro espécies, composta por dois pares predador-presa conectados, no qual o predador do primeiro par interage com presa do segundo par. A intensidade desta interação é um importante parâmetro do modelo. Exploramos o comportamento do sistema sob diferentes intensidades de acoplamento e estudamos a dinâmica de sobrevivência e extinção. Analisamos situações em que as quatro espécies têm uma população inicial inferior ao seu valor de equilíbrio, simulando situações de catástrofe em que estas abundâncias são reduzidas devido à ação humana ou mudanças ambientais. Este tipo de condição inicial faz que as populações oscilem antes de reequilibrarem, por vezes reduzindo seu valor para apenas uma pequena fração da população inicial, levando na prática à sua extinção. Nessas análises efeitos inesperados foram observados, como a sobrevivência da presa mais predada. A partir desse estudo, expandimos a rede de dois pares de predadores e presas para três, quatro e cinco pares, seguindo os mesmos conceitos de análise. Por fim, realizamos um breve estudo de uma rede de intera¸c¿oes pré-histórica, extinta no final do Pleistoceno / Abstract: All living organisms interact with individuals of its own species and also with those of other species, forming a complex network of interactions that have an important role in the preservation of the biodiversity. Understanding the underlying behavior and stability of these systems is of fundamental importance to the conservation of these resources. In this work we consider a network with only four species, comprising two predator-prey pairs connected, where the predator of the first pair interacts with the prey of the second pair. The intensity of this interaction is an important parameter of the model. We explore the system behavior under different intensities of coupling and study the dynamics of survival and extinction. We analyze situations in which the four species have initial populations smaller than the corresponding equilibrium values, simulating catastrophic events in which these abundances are reduced due to human action or environmental changes. This type of initial condition makes the populations oscillate before re-equilibrating, sometimes reducing its value to only a small fraction of the initial population, bringing them in practice to extinction. In these analysis we found unexpected effects, such as the survival of the prey that is most preyed. From this study, we expanded the network of two pairs of predators and preys to three, four and five pairs, following the same methods of analysis. Finally, we conducted a brief survey of a prehistoric network extinct in the late Pleistocene / Doutorado / Física Geral / Doutora em Ciências

The idea that emergent content generation for video games will add depth to the gameplay experience is something often mentioned. With this article I want to make a connection between the science of complex systems and emergence, and the area of video game research and development. Not only does emergent content generation add depth to gameplay experience, it would also reduce the stress on developers, if diverse content could be generated automatically. I have conducted a keyword search on 412 articles from renown conferences with the following keywords: complex system", "emerg", and "spontaneous". The results show that while emergence is quite popular in the fi eld of video game research, complex system as a term is not.

La description et la compréhension d'un système passe souvent par la construction d'un modèle mathématique. Ce dernier constitue un point de vue particulier sur le système (structurel, dynamique, etc.). Constituer des modèle splus complets, c'est-à-dire multi-point-de-vue, atteint rapidement les limites des formalismes qui les supportent. Une solution alternative passe par le couplage de plusieurs modèles «simples». Dans le cas où chaque modèle correspond à un niveau de description du système, comme le niveau de la molécule, le niveau de la cellule, le niveau de l'organe, pour un système biologique, nous parlerons de modélisation multi-niveau. Ces niveaux sont organisés et interagissent. Nous pensons que la modélisation multi-niveau ouvre une voie prometteuse pour l'étude des systèmes complexes, traditionnellement durs à modéliser.Nous explorons trois voies pour la compréhension du fonctionnement de ces modèles en nous restreignant à la question de la relation entre global et local, c'est à dire entre l'individu et la population. La première voie est formelle et passe par la définition mathématique de «modèle» indépendamment du formalisme qui le supporte, par la présentation des différents types de modèles que l'on peut construire et par la définition explicite des relations qu'ils entretiennent.La seconde voie est portée par l'activité, définie dans le cadre de mgs, un langage de programmation spatiale, dont le modèle de calcul est fondé sur la réécriture des collections topologiques au moyen de transformations. Nous fournissons une méthode constructive pour l'obtention d'une description de plus haut niveau (une abstraction) des systèmes étudiés en déterminant automatiquement quelle est la sous-collection active sans la nécessité de faire référence à la sous-collection quiescente.La dernière voie est pratique, elle passe par la programmation de otb, un outil de simulation parallèle pour l'étude de la morphogénèse dans une population de bactéries ecoli. Pour otb, nous avons conçu un algorithme générique de calcul parallèle d'un automate cellulaire en deux dimensions, adapté aux cartesgraphiques grand public. Le modèle embarqué dans otb correspond au couplage de trois modèles correspondant chacun à un niveau de description du système: le modèle physique, qui décrit la dynamique des collisions entre bactéries, le modèle chimique, qui décrit la réaction et la diffusion des morphogènes, et le modèle de prise de décision, qui décrit l'interaction entre les bactéries et leur support / We often build mathematical models to describe and understand what a systemdoes.Each model gives a specific point of view on the system (structure, dynamics,etc.).Building more comprehensive models that encompass many different points of viewis limited by the formalism they are written in.Coupling “simple” models to form a bigger one is an alternative.If each model corresponds to a level of description of the system, e.g., themolecular level, the cellular level, the organ level in biology, then we callthis technique multi-level modelling.Levels of description are organized and interact with each other.We think that multi-level modelling is a promising technique to model complexsystems, which are known to be difficult to model.We have opened three distinct research tracks to investigate the link betweenlocal and global properties, for instance between those of an entity and itspopulation — a classical opposition in complex systems.On the first track, we give precise definitions of a model — independentlyof its underlying formalism, of a system and of some of the relations modelshave (validation, abstraction, composition).We also introduce different classes of models and show how they relate to someclassical definitions (dynamic models, spatial models, etc.)On the second track, we look at mgs, a spatial programming language based onthe rewriting of topological collections by means of transformation functions.We present a constructive method giving us access to a higher level ofdescription of the system (an abstraction). This method automatically computesthe active sub-collection of a model, without any knowledge about the quiescentsub-collection, and follows it for each time step.Finally, on the third track, we present otb, a parallel simulator for thestudy of morphogenesis in a population of ecoli bacteria. We provide a genericalgorithm for the parallel simulation of two-dimensional cellular automataon general-purpose graphics cards.otb itself is built around a multi-level model for the population of bacteria.This model is the result of the coupling of three “simple” (base) models: aphysical model, describing how bacteria collide, a chemical model, describinghow morphogenes react and diffuse, and a decision model, describing how bacteriaand their environment interact

There is a potential as well as a growing interest amongst researchers to utilise simulation in optimising maintenance systems. The state of the art in simulation-based optimisation of maintenance was established by systematically classifying the published literature and outlining main trends in modelling and optimising maintenance systems. In general, approaches to optimise maintenance varied significantly in the literature. Overall, these studies highlight the need for a framework that unifies the approach to optimising maintenance systems. Framework requirements were established through two main sources of published research. Surveys on maintenance simulation optimisation were examined to document comments on the approaches authors follow while optimising maintenance systems. In addition, advanced and future maintenance strategies were documented to ensure it can be accommodated in the proposed framework. The proposed framework was developed using a standard flowchart tool due to its familiarity and ability to depict decision structures clearly. It provides a systematic methodology that details the steps required to connect the simulation model to an optimisation engine. Not only it provides guidance in terms of formulating the optimal problem for the maintenance system at hand but it also provides support and assistance in defining the optimisation scope and investigating applicable maintenance strategies. Additionally, it considers current issues relating to maintenance systems both in research and in practice such as uncertainty, complexity and multi-objective optimisation. The proposed framework cannot be applied using existing approaches for modelling maintenance. Existing modelling approaches using simulation have a number of limitations: The maintenance system is modelled separately from other inter-related systems such as production and spare parts logistics. In addition, these approaches are used to model one maintenance strategy only. A novel approach for modelling maintenance using Discrete Event Simulation is proposed. The proposed approach enables the modelling of interactions amongst various maintenance strategies and their effects on the assets in non-identical multi-unit systems. Using the proposed framework and modelling approach, simulation-based optimisation was conducted on an academic case and two industrial cases that are varied in terms of sector, size, number of manufacturing processes and level of maintenance documentation. Following the structured framework enabled discussing and selecting the suitable optimisation scope and applicable maintenance strategies as well as formulating a customised optimal problem for each case. The results of the study suggest that over-looking the optimisation of maintenance strategies may lead to sub-optimal solutions. In addition, this research provides insights for non-conflicting objectives in maintenance systems.

Two well-known methods of improving the reliability of a system are (i) provision of redundant units, and (ii) repair maintenance. In a redundant system more units are made available for performing the sys- tem function when fewer are required actually. There are two major of types of redundancy - parallel and standby. In this thesis we are concerned with both these types. Some of the typical assumptions made in the analysis of redundant systems are 1. the life time and the repair time distributions are assumed to be exponential 2. the repair rate is assumed to be constant 3. the repairman is assumed to be perfect, and hence go with only one repairman 4. the repair facility can take up a failed unit for repair at any time, if no other unit is undergoing repair 5. the system under consideration is needed all the time 6. usage of only conventional methods for the analysis of the estimated reliability of systems. However, we frequently come across systems where one or more of these assumptions have to be dropped. This is the motivation for the detailed study of the models presented in this thesis. In this thesis we present several models of redundant systems relaxing one or more of these assumptions simultaneously. More specifically it is a study of stochastic models of redundant repairable systems with non-exponential life time and repair times, varying repair rate, different types of repairmen, intermittent use and the use of time series in reliability modelling. The thesis contains seven chapters. Chapter 1 is introductory in nature and contains a brief description of the mathematical techniques used in the analysis of redundant systems. In chapter 2 assumption (1) is relaxed while studying two models with the assumption of life times and repair times to follow bivariate exponential distributions. Various operating characteristics have been obtained and the confidence limits have been established analytically for the system measure, availability for both the models. Reliability analysis of a two unit standby system with varying repair rate is studied in chapter 3, by relaxing the assumption (2). In this chapter a similar study of chapter 2 is studied with assumption that the repair time distribution is generalised Erlangian. Assumption (3) is relaxed in chapter 4, and we introduced two repairman (one regular repairman and the other expert repairman) to so that the system will be more efficient. The asymptotic confidence limits are obtained for the study state availability of such a system. A three-unit system in which the ”preparation time” is introduced, and hence the assumption (4) is relaxed in this chapter 5. The difference-differential equations for the state probabilities are derived. The confidence limits for the steady state availability are obtained analytically and illustrated numerically. In chapter 6, assumption (5) is relaxed. An intermittently used k our of n:F system with a single repair facility is condered with the assumption that failures will not be detected during a no need period. Identifying regeneration points expressions are derived for the survivor function of the time to the first disappointment and the mean number of disappointments and the sys- tem recoveries in an interval. Expressions are also deduced for the stationary rate of occurrence of these events. Chapter 7 presents an unconventional but powerful method for the analysis of the estimated reliability of systems constituted of subsystems (compo- nents) operating in series and/or in parallel under varying operational and environmental conditions. In this chapter assumption (vi) is relaxed. The proposed method construes the estimated reliability data as time series which are analysed using the well-known time series techniques. / Thesis (PhD (Industrial Systems))--University of Pretoria, 2006. / Industrial and Systems Engineering / unrestricted

Complex systems offer broad, unique research challenges due to their inability to be understood through a classic reductionist perspective, as they exhibit emergent phenomena that arise through the interactions of their components. In this thesis, we briefly review some characteristics of complex systems and the interplay of mathematical and computational methods to study them. We then discuss these approaches, how they are implemented, and how they support one another in three settings. First, we present a study that connects weather data to seasonal population-abundance of mosquitoes, using a microscopic model. Secondly, we consider the collective motions that arise in ensembles of disks interacting through non-elastic collisions and investigate how such behaviors affect macroscopic transport properties. Finally, we consider a 'self-sorting' one-dimensional collection of point-particles. In all of these cases, agent-based models and simulations are used to guide analysis, and in the final example, we explain how the simulations led to new theorems. Articles and molecular dynamics computer codes are provided as appendices.

Plus de 50% de la population mondiale vit dans des zones urbaines et cette proportion devrait augmenter dans les prochaines décennies. Comprendre ce qui régit l'évolution des systèmes urbains est donc devenu d'une importance fondamentale. Ce renouveau d'intérêt combiné avec la disponibilité de données à grande échelle, permet d'entrevoir l'avènement d'une nouvelle science des villes, interdisciplinaire et basée sur les données.Des études récentes ont montré l'existence de régularités statistiques et de lois d'échelle pour plusieurs indicateurs socio-économiques, tels que la consommation d'essence, la distance moyenne parcourue quotidiennement, le cout des infrastructures, etc. Malgré plusieurs tentatives récentes, la compréhension théorique de ces résultats observés empiriquement demeure très partielle.Le but de cette thèse est d'obtenir une modélisation simplifiée, hors-équilibre de la croissance urbaine, en s'appuyant sur un petit nombre de mécanismesimportants et qui fournit des prédictions quantitatives en accord avec lesdonnées empiriques. Pour cela, nous nous inspirerons des études en géographiequantitative et en économie spatiale et nous revisiterons certains de ces anciens modèles avec une nouvelle approche intégrant les outils et concepts de la physique. / More than 50 % of the world population lives in urban areas and this proportion is expected to increase in the coming decades. Understanding what governs the evolution of urban systems has thus become of paramount importance.This renewed interest combined with the availability of large-scale data, allows a glimpse into the dawn of a new science of cities, interdisciplinary and based on data.Recent studies have shown the existence of statistical regularities and scaling laws for several socio-economic indicators such as fuel consumption, average commuting distance, cost of infrastructure, etc., and despite several recent attempts, the theoretical understanding of these results empirically observed remains very partial. The purpose of this thesis is to obtain a simplified, out of equilibrium model of urban growth, based on a small number of important mechanisms and which provides quantitative predictions in agreement with empirical data. For this, we will draw on studies in quantitative geography and spatial economy and we will revisit some of these old models with a new approach that integrates the tools and concepts of physics.

No description available.

Stigmergy refers to indirect communication that was originally found in biological systems. It is used for self-organization by ants, bees, and flocks of birds, by allowing individuals to focus on local information. Through local communication among individuals, larger patterns are formed without centralized communication. This self-organization is just one type of system studied within complex systems. Systems of ants, bees, and flocks of birds are considered complex because they exhibit emergent behavior: the outcome is more than the sum of the individual parts. Emergent behavior can be found in many other systems as well. One example is the Internet, which is a series of computers organized in a self-organized fashion. Complexity can also be defined through properties other than emergent behavior, such as existing on multiple scales. Many biological systems are multi-scale. For instance, cancer exists on many scales, including the sub-cellular and cellular levels. Many computing systems are also multi-scale, as there may be both individual and system-wide controls interacting together to determine the output. Many multi-agent systems would fall into this category, as would many large software systems. In this dissertation I examine complex systems in artificial intelligence and biology: the growth of cancer, population dynamics, emotions, multi-agent fault tolerance, and real-time strategic AI for games. My goal is twofold: a) to develop novel computational models of complex biological systems, and b) to tackle key AI research questions by proposing new algorithms and techniques that are inspired by those complex biological systems. In all of these cases I design variations on stigmergic communication to accomplish the task at hand. My contributions are a new agent-based cancer growth model, a proposed use of location communication for removing cancer, improved multi-agent fault tolerance through localized messaging, a new approach to modeling predator-prey dynamics using computational emotions, and improved strategic game AI through computational emotions.