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The Evolution of Electronic Procurement: Transforming Business as Usual
by Tobias SchoenherrThis book responds to the increasing speed with which the domain of electronic procurement has been evolving, as well to the significant advances predicted to take place in the near future. Covering the fundamentals of electronic procurement as well as advanced applications, the main focus is on the critical importance of information technology for modern supply management professionals. Tracing the evolution of electronic procurement over the last 20 years, the book illustrates how the concept has evolved from a novel idea into a standard approach that cannot be neglected, fundamentally transforming business as usual. The transformation is highlighted by the evolution of online reverse auctions, as well as the ensuing expansion of technology to virtually all aspects of strategic sourcing in the form of integrated electronic sourcing suites. Several advances and new applications of electronic procurement are presented, with an emphasis on how social media can be leveraged for supply management and its associated significant potential.
The Evolution of Pervasive Information Systems
by Carine Souveyet Manuele Kirsch Pinheiro Philippe Roose Luiz Angelo SteffenelThis book covers several aspects related the evolution of Information Systems into Pervasive Information Systems. New IT trends have an important impact on IT infrastructures, which become increasingly heterogeneous, flexible, and dynamic. These new trends are transforming Information Systems into what we call Pervasive Information Systems. The purpose of this book is to combine “state-of-the-art” solutions from various research communities (such as Information Systems Engineering, Cloud Computing, Fog/Edge Computing, Pervasive systems, Distributed systems, and Middleware systems) related to the Pervasive Information Systems emergence as a common point of view. Through these multiple contributions, this book tackles important challenges concerning Information Systems evolution, promoting a holistic view of Pervasive Information System.Pervasive Information Systems (PIS) can be defined as a new class of Information Systems. It can be characterized by an IT that is gradually embedded in the physical environment and can accommodate the user’s requirements and desires when necessary. This evolution implies considering Information Systems beyond the organization's physical environment to integrate new technologies transparently, leading to a pervasive environment whose behavior should be more and more reactive & proactive. It corresponds to an important change in Information Systems Engineering. Pervasive Information Systems are deeply multidisciplinary systems, demanding a holistic view in which multiple domains are invited to contribute.
The Evolution of Policing: Worldwide Innovations and Insights (International Police Executive Symposium Co-Publications)
by Melchor C. de Guzman Aiedeo Mintie Das Dilip K. DasDrawn from recent proceedings of the International Police Executive Symposium (IPES), this volume explores major policing initiatives and evolutions across the globe and presents practical insights on how police are retooling their profession. The book discusses the trends in evolving police roles among democratic and democratizing states, the impact of community-oriented policing, innovations occurring in police training and management, and issues relating to ethics, technology, investigations, and handling public relations. The book also examines challenges to police practices, such as terrorism, decentralization, and the policing of indigenous and special population groups.
Evolution of Semantic Systems
by Bernd-Olaf Küppers Stefan Artmann Udo HahnComplex systems in nature and society make use of information for the development of their internal organization and the control of their functional mechanisms. Alongside technical aspects of storing, transmitting and processing information, the various semantic aspects of information, such as meaning, sense, reference and function, play a decisive part in the analysis of such systems. With the aim of fostering a better understanding of semantic systems from an evolutionary and multidisciplinary perspective, this volume collects contributions by philosophers and natural scientists, linguists, information and computer scientists. They do not follow a single research paradigm; rather they shed, in a complementary way, new light upon some of the most important aspects of the evolution of semantic systems. Evolution of Semantic Systems is intended for researchers in philosophy, computer science, and the natural sciences who work on the analysis or development of semantic systems, ontologies, or similar complex information structures. In the eleven chapters, they will find a broad discussion of topics ranging from underlying universal principles to representation and processing aspects to paradigmatic examples.
Evolution of Smart Sensing Ecosystems with Tamper Evident Security
by Pawel Sniatala S.S. Iyengar Sanjeev Kaushik RamaniThis book presents an overview on security and privacy issues in dynamic sensor networks and Internet of Things (IoT) networks and provides a novel tamper evident technique to counter and defend against these security related issues. The mission of this book is to explain the evolution of techniques and strategies in securing information transfer and storage thus facilitating a digital transition towards the modern tamper evident systems. The goal is also to aid business organizations that are dependent on the analysis of the large volumes of generated data in securing and addressing the associated growing threat of attackers relentlessly waging attacks and the challenges in protecting the confidentiality, integrity and provenance of data. The book also provides a comprehensive insight into the secure communication techniques and tools that have evolved and the impact they have had in supporting and flourishing the business through the cyber era. This book also includes chapters that discuss the most primitive encryption schemes to the most recent use of homomorphism in ensuring the privacy of the data thus leveraging greater use of new technologies like cloud computing and others.
Evolution of STEM-Driven Computer Science Education: The Perspective of Big Concepts
by Vytautas Štuikys Renata BurbaitėThe book discusses the evolution of STEM-driven Computer Science (CS) Education based on three categories of Big Concepts, Smart Education (Pedagogy), Technology (tools and adequate processes) and Content that relates to IoT, Data Science and AI. For developing, designing, testing, delivering and assessing learning outcomes for K-12 students (9-12 classes), the multi-dimensional modelling methodology is at the centre. The methodology covers conceptual and feature-based modelling, prototyping, and virtual and physical modelling at the implementation and usage level. Chapters contain case studies to assist understanding and learning. The book contains multiple methodological and scientific innovations including models, frameworks and approaches to drive STEM-driven CS education evolution.Educational strategists, educators, and researchers will find valuable material in this book to help them improve STEM-driven CS education strategies, curriculum development, and new ideas for research.
The Evolution of the Chinese Internet: Creative Visibility in the Digital Public
by Shaohua GuoDespite widespread consensus that China's digital revolution was sure to bring about massive democratic reforms, such changes have not come to pass. While scholars and policy makers alternate between predicting change and disparaging a stubbornly authoritarian regime, in this book Shaohua Guo demonstrates how this dichotomy misses the far more complex reality. The Evolution of the Chinese Internet traces the emergence and maturation of one of the most creative digital cultures in the world through four major technological platforms: the bulletin board system, the blog, the microblog, and WeChat. Guo transcends typical binaries of freedom and control, to argue that Chinese Internet culture displays a uniquely sophisticated interplay between multiple extremes, and that its vibrancy is dependent on these complex negotiations. In contrast to the flourishing of research findings on what is made invisible online, this book examines the driving mechanisms that grant visibility to particular kinds of user-generated content. Offering a systematic account of how and why an ingenious Internet culture has been able to thrive, Guo highlights the pivotal roles that media institutions, technological platforms, and creative practices of Chinese netizens have played in shaping culture on- and offline.
The Evolution of the Image: Political Action and the Digital Self (Routledge Advances in Art and Visual Studies)
by Marco Bohr Basia SliwinskaThis volume addresses the evolution of the visual in digital communities, offering a multidisciplinary discussion of the ways in which images are circulated in digital communities, the meanings that are attached to them and the implications they have for notions of identity, memory, gender, cultural belonging and political action. Contributors focus on the political efficacy of the image in digital communities, as well as the representation of the digital self in order to offer a fresh perspective on the role of digital images in the creation and promotion of new forms of resistance, agency and identity within visual cultures.
Evolutionary Algorithms
by Alain Petrowski Sana Ben-HamidaEvolutionary algorithms are bio-inspired algorithms based on Darwin’s theory of evolution. They are expected to provide non-optimal but good quality solutions to problems whose resolution is impracticable by exact methods. In six chapters, this book presents the essential knowledge required to efficiently implement evolutionary algorithms. Chapter 1 describes a generic evolutionary algorithm as well as the basic operators that compose it. Chapter 2 is devoted to the solving of continuous optimization problems, without constraint. Three leading approaches are described and compared on a set of test functions. Chapter 3 considers continuous optimization problems with constraints. Various approaches suitable for evolutionary methods are presented. Chapter 4 is related to combinatorial optimization. It provides a catalog of variation operators to deal with order-based problems. Chapter 5 introduces the basic notions required to understand the issue of multi-objective optimization and a variety of approaches for its application. Finally, Chapter 6 describes different approaches of genetic programming able to evolve computer programs in the context of machine learning.
Evolutionary Algorithms and Metaheuristics in Civil Engineering and Construction Management
by Jorge Magalhães-Mendes David GreinerThis book focuses on civil and structural engineering and construction management applications. The contributions constitute modified, extended and improved versions of research presented at the minisymposium organized by the editors at the ECCOMAS conference on this topic in Barcelona 2014.
Evolutionary Algorithms and Neural Networks: Theory and Applications (Studies in Computational Intelligence #780)
by Seyedali MirjaliliThis book introduces readers to the fundamentals of artificial neural networks, with a special emphasis on evolutionary algorithms. At first, the book offers a literature review of several well-regarded evolutionary algorithms, including particle swarm and ant colony optimization, genetic algorithms and biogeography-based optimization. It then proposes evolutionary version of several types of neural networks such as feed forward neural networks, radial basis function networks, as well as recurrent neural networks and multi-later perceptron. Most of the challenges that have to be addressed when training artificial neural networks using evolutionary algorithms are discussed in detail. The book also demonstrates the application of the proposed algorithms for several purposes such as classification, clustering, approximation, and prediction problems. It provides a tutorial on how to design, adapt, and evaluate artificial neural networks as well, and includes source codes for most of the proposed techniques as supplementary materials.
Evolutionary Algorithms for Food Science and Technology
by Alberto Tonda Evelyne Lutton Nathalie PerrotResearchers and practitioners in food science and technology routinely face several challenges, related to sparseness and heterogeneity of data, as well as to the uncertainty in the measurements and the introduction of expert knowledge in the models. Evolutionary algorithms (EAs), stochastic optimization techniques loosely inspired by natural selection, can be effectively used to tackle these issues. In this book, we present a selection of case studies where EAs are adopted in real-world food applications, ranging from model learning to sensitivity analysis.
Evolutionary Algorithms for Mobile Ad Hoc Networks
by Yoann Pigné Grégoire Danoy Pascal Bouvry Bernabé Dorronsoro Patricia RuizDescribes how evolutionary algorithms (EAs) can be used to identify, model, and minimize day-to-day problems that arise for researchers in optimization and mobile networkingMobile ad hoc networks (MANETs), vehicular networks (VANETs), sensor networks (SNs), and hybrid networks--each of these require a designer's keen sense and knowledge of evolutionary algorithms in order to help with the common issues that plague professionals involved in optimization and mobile networking.This book introduces readers to both mobile ad hoc networks and evolutionary algorithms, presenting basic concepts as well as detailed descriptions of each. It demonstrates how metaheuristics and evolutionary algorithms (EAs) can be used to help provide low-cost operations in the optimization process--allowing designers to put some "intelligence" or sophistication into the design. It also offers efficient and accurate information on dissemination algorithms, topology management, and mobility models to address challenges in the field.Evolutionary Algorithms for Mobile Ad Hoc Networks:Instructs on how to identify, model, and optimize solutions to problems that arise in daily researchPresents complete and up-to-date surveys on topics like network and mobility simulatorsProvides sample problems along with solutions/descriptions used to solve each, with performance comparisonsCovers current, relevant issues in mobile networks, like energy use, broadcasting performance, device mobility, and moreEvolutionary Algorithms for Mobile Ad Hoc Networks is an ideal book for researchers and students involved in mobile networks, optimization, advanced search techniques, and multi-objective optimization.
Evolutionary Algorithms, Swarm Dynamics and Complex Networks
by Ivan Zelinka Guanrong ChenEvolutionary algorithms constitute a class of well-known algorithms, which are designed based on the Darwinian theory of evolution and Mendelian theory of heritage. They are partly based on random and partly based on deterministic principles. Due to this nature, it is challenging to predict and control its performance in solving complex nonlinear problems. Recently, the study of evolutionary dynamics is focused not only on the traditional investigations but also on the understanding and analyzing new principles, with the intention of controlling and utilizing their properties and performances toward more effective real-world applications. In this book, based on many years of intensive research of the authors, is proposing novel ideas about advancing evolutionary dynamics towards new phenomena including many new topics, even the dynamics of equivalent social networks. In fact, it includes more advanced complex networks and incorporates them with the CMLs (coupled map lattices), which are usually used for spatiotemporal complex systems simulation and analysis, based on the observation that chaos in CML can be controlled, so does evolution dynamics. All the chapter authors are, to the best of our knowledge, originators of the ideas mentioned above and researchers on evolutionary algorithms and chaotic dynamics as well as complex networks, who will provide benefits to the readers regarding modern scientific research on related subjects.
Evolutionary and Biologically Inspired Music, Sound, Art and Design
by Colin Johnson Adrian Carballal João CorreiaThis book constitutes the refereed proceedings of the 4th International Conference on Biologically Inspired Music, Sound, Art and Design, EvoMUSART 2015, held in Copenhagen, Denmark, in April 2015, co-located with the Evo* 2015 events EuroGP, EvoCOP and Evo Applications. The 23 revised full papers presented were carefully reviewed and selected from 43 submissions. They cover a wide range of topics and application areas, including generative approaches to music, graphics, game content and narrative; music information retrieval; computational aesthetics; the mechanics of interactive evolutionary computation and the art theory of evolutionary computation.
Evolutionary and Deterministic Methods for Design Optimization and Control With Applications to Industrial and Societal Problems (Computational Methods in Applied Sciences #49)
by Esther Andrés-Pérez Leo M. González Jacques Periaux Nicolas Gauger Domenico Quagliarella Kyriakos GiannakoglouThis book contains thirty-five selected papers presented at the International Conference on Evolutionary and Deterministic Methods for Design, Optimization and Control with Applications to Industrial and Societal Problems (EUROGEN 2017). This was one of the Thematic Conferences of the European Community on Computational Methods in Applied Sciences (ECCOMAS). Topics treated in the various chapters reflect the state of the art in theoretical and numerical methods and tools for optimization, and engineering design and societal applications. The volume focuses particularly on intelligent systems for multidisciplinary design optimization (mdo) problems based on multi-hybridized software, adjoint-based and one-shot methods, uncertainty quantification and optimization, multidisciplinary design optimization, applications of game theory to industrial optimization problems, applications in structural and civil engineering optimum design and surrogate models based optimization methods in aerodynamic design.
Evolutionary and Memetic Computing for Project Portfolio Selection and Scheduling (Adaptation, Learning, and Optimization #26)
by Kyle Robert Harrison Saber Elsayed Ivan Leonidovich Garanovich Terence Weir Sharon G. Boswell Ruhul Amin SarkerThis book consists of eight chapters, authored by distinguished researchers and practitioners, that highlight the state of the art and recent trends in addressing the project portfolio selection and scheduling problem (PPSSP) across a variety of domains, particularly defense, social programs, supply chains, and finance. Many organizations face the challenge of selecting and scheduling a subset of available projects subject to various resource and operational constraints. In the simplest scenario, the primary objective for an organization is to maximize the value added through funding and implementing a portfolio of projects, subject to the available budget. However, there are other major difficulties that are often associated with this problem such as qualitative project benefits, multiple conflicting objectives, complex project interdependencies, workforce and manufacturing constraints, and deep uncertainty regarding project costs, benefits, and completion times.It is well known that the PPSSP is an NP-hard problem and, thus, there is no known polynomial-time algorithm for this problem. Despite the complexity associated with solving the PPSSP, many traditional approaches to this problem make use of exact solvers. While exact solvers provide definitive optimal solutions, they quickly become prohibitively expensive in terms of computation time when the problem size is increased. In contrast, evolutionary and memetic computing afford the capability for autonomous heuristic approaches and expert knowledge to be combined and thereby provide an efficient means for high-quality approximation solutions to be attained. As such, these approaches can provide near real-time decision support information for portfolio design that can be used to augment and improve existing human-centric strategic decision-making processes. This edited book provides the reader with a broad overview of the PPSSP, its associated challenges, and approaches to addressing the problem using evolutionary and memetic computing.
Evolutionary and Swarm Intelligence Algorithms (Studies in Computational Intelligence #779)
by Jagdish Chand Bansal Pramod Kumar Singh Nikhil R. PalThis book is a delight for academics, researchers and professionals working in evolutionary and swarm computing, computational intelligence, machine learning and engineering design, as well as search and optimization in general. It provides an introduction to the design and development of a number of popular and recent swarm and evolutionary algorithms with a focus on their applications in engineering problems in diverse domains. The topics discussed include particle swarm optimization, the artificial bee colony algorithm, Spider Monkey optimization algorithm, genetic algorithms, constrained multi-objective evolutionary algorithms, genetic programming, and evolutionary fuzzy systems. A friendly and informative treatment of the topics makes this book an ideal reference for beginners and those with experience alike.
Evolutionary Approach to Machine Learning and Deep Neural Networks: Neuro-Evolution and Gene Regulatory Networks
by Hitoshi IbaThis book provides theoretical and practical knowledge about a methodology for evolutionary algorithm-based search strategy with the integration of several machine learning and deep learning techniques. These include convolutional neural networks, Gröbner bases, relevance vector machines, transfer learning, bagging and boosting methods, clustering techniques (affinity propagation), and belief networks, among others. The development of such tools contributes to better optimizing methodologies. Beginning with the essentials of evolutionary algorithms and covering interdisciplinary research topics, the contents of this book are valuable for different classes of readers: novice, intermediate, and also expert readers from related fields.Following the chapters on introduction and basic methods, Chapter 3 details a new research direction, i.e., neuro-evolution, an evolutionary method for the generation of deep neural networks, and also describes how evolutionary methods are extended in combination with machine learning techniques. Chapter 4 includes novel methods such as particle swarm optimization based on affinity propagation (PSOAP), and transfer learning for differential evolution (TRADE), another machine learning approach for extending differential evolution. The last chapter is dedicated to the state of the art in gene regulatory network (GRN) research as one of the most interesting and active research fields. The author describes an evolving reaction network, which expands the neuro-evolution methodology to produce a type of genetic network suitable for biochemical systems and has succeeded in designing genetic circuits in synthetic biology. The author also presents real-world GRN application to several artificial intelligent tasks, proposing a framework of motion generation by GRNs (MONGERN), which evolves GRNs to operate a real humanoid robot.
Evolutionary Artificial Intelligence: Proceedings of ICEAI 2023 (Algorithms for Intelligent Systems)
by David Asirvatham Francisco M. Gonzalez-Longatt Przemyslaw Falkowski-Gilski R. KanthavelThis book gathers a collection of selected works and new research results of scholars and graduate students presented at International Conference on Evolutionary Artificial Intelligence (ICEAI 2023) held in Malaysia during 13-14 September 2023. The focus of the book is interdisciplinary in nature and includes research on all aspects of evolutionary computation to find effective solutions to a wide range of computationally difficult problems. The book covers topics such as particle swarm optimization, evolutionary programming, genetic programming, hybrid evolutionary algorithms, ant colony optimization, evolutionary neural networks, evolutionary reinforcement learning, genetic algorithms, memetic algorithms, novel bio-inspired algorithms, evolving multi-agent systems, agent-based evolutionary approaches, and evolutionary game theory.
Evolutionary Bioinformatics
by Donald R. ForsdykeNow in its third edition and supplemented with more online material, this book aims to make the "new" information-based (rather than gene-based) bioinformatics intelligible both to the "bio" people and the "info" people. Books on bioinformatics have traditionally served gene-hunters, and biologists who wish to construct family trees showing tidy lines of descent. While dealing extensively with the exciting topics of gene discovery and database-searching, such books have hardly considered genomes as information channels through which multiple forms and levels of information have passed through the generations. This "new bioinformatics" contrasts with the "old" gene-based bioinformatics that so preoccupies previous texts. Forms of information that we are familiar with (mental, textual) are related to forms with which we are less familiar (hereditary). The book extends a line of evolutionary thought that leads from the nineteenth century (Darwin, Butler, Romanes, Bateson), through the twentieth (Goldschmidt, White), and into the twenty first (the final works of the late Stephen Jay Gould). Long an area of controversy, diverging views may now be reconciled.
Evolutionary Biology
by Pierre PontarottiSince 1997, scientists of different disciplines sharing a deep interest in concepts and knowledge related to evolutionary biology have held the annual Evolutionary Biology Meetings in Marseille in order to discuss their research and promote collaboration. Lately scientists especially focusing on applications have also joined the group. This book starts with the report of the "12th Evolutionary Biology Meeting", which gives a general idea of the meeting's epistemological stance. This is followed by 22 chapters, a selection of the most representative contributions, which are grouped under the following four themes: Part I Concepts and Knowledge - Part II Modelization - Part III Applied Evolutionary Biology - Part IV Applications in Other Fields -Part IV transcends the field of biology, presenting applications of evolutionary biology in economics and astronomy.
Evolutionary Computation (International Series on Computational Intelligence)
by null D. Dumitrescu null Beatrice Lazzerini null Lakhmi C. Jain null A. DumitrescuRapid advances in evolutionary computation have opened up a world of applications-a world rapidly growing and evolving. Decision making, neural networks, pattern recognition, complex optimization/search tasks, scheduling, control, automated programming, and cellular automata applications all rely on evolutionary computation. Evolutionary Com
Evolutionary Computation: A Unified Approach
by Kenneth A. de JongChoice Outstanding Academic Title, 2006. Evolutionary computation, the use of evolutionary systems as computational processes for solving complex problems, is a tool used by computer scientists and engineers who want to harness the power of evolution to build useful new artifacts, by biologists interested in developing and testing better models of natural evolutionary systems, and by artificial life scientists for designing and implementing new artificial evolutionary worlds. In this clear and comprehensive introduction to the field, Kenneth De Jong presents an integrated view of the state of the art in evolutionary computation. Although other books have described such particular areas of the field as genetic algorithms, genetic programming, evolution strategies, and evolutionary programming, Evolutionary Computation is noteworthy for considering these systems as specific instances of a more general class of evolutionary algorithms. This useful overview of a fragmented field is suitable for classroom use or as a reference for computer scientists and engineers.
Evolutionary Computation 1: Basic Algorithms and Operators (Ieee Press Series On Computational Intelligence Ser. #1)
by Thomas Baeck D. B Fogel Z MichalewiczThe field of evolutionary computation is expanding dramatically, fueled by the vast investment that reflects the value of applying its techniques. Culling material from the Handbook of Evolutionary Computation, Evolutionary Computation 1: Basic Algorithms and Operators contains up-to-date information on algorithms and operators used in evolutionary computing. This volume discusses the basic ideas that underlie the main paradigms of evolutionary algorithms, evolution strategies, evolutionary programming, and genetic programming. It is intended to be used by individual researchers, teachers, and students working and studying in this expanding field.