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Modeling and Optimization in Green Logistics
by Houda Derbel Bassem Jarboui Patrick SiarryThis book presents recent work that analyzes general issues of green logistics and smart cities. The contributed chapters consider operating models with important ecological, economic, and social objectives.The content will be valuable for researchers and postgraduate students in computer science, information technology, industrial engineering, and applied mathematics.
Modeling and Optimization in Space Engineering: State of the Art and New Challenges (Springer Optimization and Its Applications #144)
by Giorgio Fasano János D. PintérThis book presents advanced case studies that address a range of important issues arising in space engineering. An overview of challenging operational scenarios is presented, with an in-depth exposition of related mathematical modeling, algorithmic and numerical solution aspects. The model development and optimization approaches discussed in the book can be extended also towards other application areas. The topics discussed illustrate current research trends and challenges in space engineering as summarized by the following list: • Next Generation Gravity Missions • Continuous-Thrust Trajectories by Evolutionary Neurocontrol • Nonparametric Importance Sampling for Launcher Stage Fallout • Dynamic System Control Dispatch • Optimal Launch Date of Interplanetary Missions • Optimal Topological Design • Evidence-Based Robust Optimization • Interplanetary Trajectory Design by Machine Learning • Real-Time Optimal Control • Optimal Finite Thrust Orbital Transfers • Planning and Scheduling of Multiple Satellite Missions • Trajectory Performance Analysis • Ascent Trajectory and Guidance Optimization • Small Satellite Attitude Determination and Control • Optimized Packings in Space Engineering • Time-Optimal Transfers of All-Electric GEO Satellites Researchers working on space engineering applications will find this work a valuable, practical source of information. Academics, graduate and post-graduate students working in aerospace, engineering, applied mathematics, operations research, and optimal control will find useful information regarding model development and solution techniques, in conjunction with real-world applications.
Modeling and Optimization in Space Engineering
by Giorgio Fasano János D. PintérThis volume presents a selection of advanced case studies that address a substantial range of issues and challenges arising in space engineering. The contributing authors are well-recognized researchers and practitioners in space engineering and in applied optimization. The key mathematical modeling and numerical solution aspects of each application case study are presented in sufficient detail. Classic and more recent space engineering problems - including cargo accommodation and object placement, flight control of satellites, integrated design and trajectory optimization, interplanetary transfers with deep space manoeuvres, low energy transfers, magnetic cleanliness modeling, propulsion system design, sensor system placement, systems engineering, space traffic logistics, and trajectory optimization - are discussed. Novel points of view related to computational global optimization and optimal control, and to multidisciplinary design optimization are also given proper emphasis. A particular attention is paid also to scenarios expected in the context of future interplanetary explorations. Modeling and Optimization in Space Engineering will benefit researchers and practitioners working on space engineering applications. Academics, graduate and post-graduate students in the fields of aerospace and other engineering, applied mathematics, operations research and optimal control will also find the book useful, since it discusses a range of advanced model development and solution techniques and tools in the context of real-world applications and new challenges.
Modeling and Optimization of Air Traffic
by Daniel Delahaye Stéphane PuechmorelThis book combines the research activities of the authors, both of whom are researchers at Ecole Nationale de l’Aviation Civile (French National School of Civil Aviation), and presents their findings from the last 15 years. Their work uses air transport as its focal point, within the realm of mathematical optimization, looking at real life problems and theoretical models in tandem, and the challenges that accompany studying both approaches. The authors’ research is linked with the attempt to reduce air space congestion in Western Europe, USA and, increasingly, Asia. They do this through studying stochastic optimization (particularly artificial evolution), the sectorization of airspace, route distribution and takeoff slots, and by modeling airspace congestion. Finally, the authors discuss their short, medium and long term research goals. They hope that their work, although related to air transport, will be applied to other fields, such is the transferable nature of mathematical optimization. At the same time, they intend to use other areas of research, such as approximation and statistics to complement their continued inquiry in their own field. Contents 1. Introduction. Part 1. Optimization and Artificial Evolution 2. Optimization: State of the Art. 3. Genetic Algorithms and Improvements. 4. A new concept for Genetic Algorithms based on Order Statistics. Part 2. Applications to Air Traffic Control 5. Air Traffic Control. 6. Contributions to Airspace Sectorization. 7. Contribution to Traffic Assignment. 8. Airspace Congestion Metrics. 9. Conclusion and Future Perspectives. About the Authors Daniel Delahaye works for Ecole Nationale de l’Aviation Civile (French National School of Civil Aviation) in France. Stéphane Puechmorel works for Ecole Nationale de l’Aviation Civile (French National School of Civil Aviation) in France.
Modeling and Optimization of Cloud-Ready and Content-Oriented Networks
by Krzysztof WalkowiakThisbook focuses on modeling and optimization of cloud-ready and content-orientednetworks in the context of different layers and accounts for specificconstraints following from protocols andtechnologies used in a particular layer. It addresses a wide range ofadditional constraints importantin contemporary networks, including various types of network flows,survivability issues, multi-layer networking, and resource location. Thebook presents recent existing and new results in a comprehensive and cohesiveway. The contents of the book are organized in five chapters, which are mostlyself-contained. Chapter 1 briefly presents information oncloud computing and content-oriented services, and introduces basic notionsand concepts of network modeling and optimization. Chapter 2 covers various optimizationproblems that arise in the context of connection-oriented networks. Chapter3 focuses on modeling and optimization of Elastic Optical Networks. Chapter 4 isdevoted to overlay networks. The book concludes with Chapter 5, summarizing thebook and present recent research trends in the field of network optimization.
Modeling and Optimization of Parallel and Distributed Embedded Systems
by Ann Gordon-Ross Sanjay Ranka Arslan MunirThis book introduces the state-of-the-art in research in parallel and distributed embedded systems, which have been enabled by developments in silicon technology, micro-electro-mechanical systems (MEMS), wireless communications, computer networking, and digital electronics. These systems have diverse applications in domains including military and defense, medical, automotive, and unmanned autonomous vehicles. The emphasis of the book is on the modeling and optimization of emerging parallel and distributed embedded systems in relation to the three key design metrics of performance, power and dependability. Key features: Includes an embedded wireless sensor networks case study to help illustrate the modeling and optimization of distributed embedded systems. Provides an analysis of multi-core/many-core based embedded systems to explain the modeling and optimization of parallel embedded systems. Features an application metrics estimation model; Markov modeling for fault tolerance and analysis; and queueing theoretic modeling for performance evaluation. Discusses optimization approaches for distributed wireless sensor networks; high-performance and energy-efficient techniques at the architecture, middleware and software levels for parallel multicore-based embedded systems; and dynamic optimization methodologies. Highlights research challenges and future research directions. The book is primarily aimed at researchers in embedded systems; however, it will also serve as an invaluable reference to senior undergraduate and graduate students with an interest in embedded systems research.
Modeling and Optimization of Signals Using Machine Learning Techniques
by Rathishchandra R. Gatti Chandra Singh K.V.S.S.S.S. Sairam Manjunatha Badiger Naveen Kumar S. Varun SaxenaExplore the power of machine learning to revolutionize signal processing and optimization with cutting-edge techniques and practical insights in this outstanding new volume from Scrivener Publishing. Modeling and Optimization of Signals using Machine Learning Techniques is designed for researchers from academia, industries, and R&D organizations worldwide who are passionate about advancing machine learning methods, signal processing theory, data mining, artificial intelligence, and optimization. This book addresses the role of machine learning in transforming vast signal databases from sensor networks, internet services, and communication systems into actionable decision systems. It explores the development of computational solutions and novel models to handle complex real-world signals such as speech, music, biomedical data, and multimedia. Through comprehensive coverage of cutting-edge techniques, this book equips readers with the tools to automate signal processing and analysis, ultimately enhancing the retrieval of valuable information from extensive data storage systems. By providing both theoretical insights and practical guidance, the book serves as a comprehensive resource for researchers, engineers, and practitioners aiming to harness the power of machine learning in signal processing. Whether for the veteran engineer, scientist in the lab, student, or faculty, this groundbreaking new volume is a valuable resource for researchers and other industry professionals interested in the intersection of technology and agriculture.
Modeling and Simulating Bodies and Garments
by Nadia Magnenat-ThalmannThe book presents all aspects of body and garment modeling for animated virtual humans. It describes how we can define fast and precise human body shapes, either from input dimensions or from body scans, how we can use predefined motions and retarget them, how we can easily create 3D garments from 2D patterns and animate them, and how we can retarget interactively various garment sizes while giving new body dimensions. A case study presents the making of the award winning film ' High Fashion in Equations'. Finally, the book describes how simulation processes can be applied to the garment industry and how we interact with an online platform for virtual clothing. This book is truly interdisciplinary as it describes the technical concepts as well as the design aspects and the problems of the clothing industry to be solved today.
Modeling and Simulating Command and Control
by Tag Gon Kim Il-Chul Moon Kathleen M. CarleyCommanding and controlling organizations in extreme situations is a challenging task in military, intelligence, and disaster management. Such command and control must be quick, effective, and considerate when dealing with the changing, complex, and risky conditions of the situation. To enable optimal command and control under extremes, robust structures and efficient operations are required of organizations. This work discusses how to design and conduct virtual experiments on resilient organizational structures and operational practices using modeling and simulation. The work illustrates key aspects of robustly networked organizations and modeled performance of human decision-makers through examples of naval-air defense, counterterrorism operations, and disaster responses.
Modeling and Simulating Complex Business Perceptions: Using Graphical Models and Fuzzy Cognitive Maps (Fuzzy Management Methods)
by Zoumpolia DikopoulouFuzzy cognitive maps (FCMs) have gained popularity in the scientific community due to their capabilities in modeling and decision making for complex problems.This book presents a novel algorithm called glassoFCM to enable automatic learning of FCM models from data. Specifically, glassoFCM is a combination of two methods, glasso (a technique originated from machine learning) for data modeling and FCM simulation for decision making. The book outlines that glassoFCM elaborates simple, accurate, and more stable models that are easy to interpret and offer meaningful decisions. The research results presented are based on an investigation related to a real-world business intelligence problem to evaluate characteristics that influence employee work readiness.Finally, this book provides readers with a step-by-step guide of the 'fcm' package to execute and visualize their policies and decisions through the FCM simulation process.
Modeling and Simulating Software Architectures: The Palladio Approach
by Heiko Koziolek Robert Heinrich Max Kramer Jens Happe Ralf H. Reussner Klaus Krogmann Steffen Becker Anne KoziolekToo often, software designers lack an understanding of the effect of design decisions on such quality attributes as performance and reliability. This necessitates costly trial-and-error testing cycles, delaying or complicating rollout. This book presents a new, quantitative architecture simulation approach to software design, which allows software engineers to model quality of service in early design stages. It presents the first simulator for software architectures, Palladio, and shows students and professionals how to model reusable, parametrized components and configured, deployed systems in order to analyze service attributes.The text details the key concepts of Palladio's domain-specific modeling language for software architecture quality and presents the corresponding development stage. It describes how quality information can be used to calibrate architecture models from which detailed simulation models are automatically derived for quality predictions. Readers will learn how to approach systematically questions about scalability, hardware resources, and efficiency. The text features a running example to illustrate tasks and methods as well as three case studies from industry. Each chapter ends with exercises, suggestions for further reading, and "takeaways" that summarize the key points of the chapter. The simulator can be downloaded from a companion website, which offers additional material. The book can be used in graduate courses on software architecture, quality engineering, or performance engineering. It will also be an essential resource for software architects and software engineers and for practitioners who want to apply Palladio in industrial settings.
Modeling and Simulating Software Architectures: The Palladio Approach
by Ralf H. Reussner Steffen Becker Jens Happe Robert Heinrich Anne KoziolekA new, quantitative architecture simulation approach to software design that circumvents costly testing cycles by modeling quality of service in early design states.Too often, software designers lack an understanding of the effect of design decisions on such quality attributes as performance and reliability. This necessitates costly trial-and-error testing cycles, delaying or complicating rollout. This book presents a new, quantitative architecture simulation approach to software design, which allows software engineers to model quality of service in early design stages. It presents the first simulator for software architectures, Palladio, and shows students and professionals how to model reusable, parametrized components and configured, deployed systems in order to analyze service attributes.The text details the key concepts of Palladio's domain-specific modeling language for software architecture quality and presents the corresponding development stage. It describes how quality information can be used to calibrate architecture models from which detailed simulation models are automatically derived for quality predictions. Readers will learn how to approach systematically questions about scalability, hardware resources, and efficiency. The text features a running example to illustrate tasks and methods as well as three case studies from industry. Each chapter ends with exercises, suggestions for further reading, and “takeaways” that summarize the key points of the chapter. The simulator can be downloaded from a companion website, which offers additional material. The book can be used in graduate courses on software architecture, quality engineering, or performance engineering. It will also be an essential resource for software architects and software engineers and for practitioners who want to apply Palladio in industrial settings.
Modeling and Simulation: Stochastic And Control Systems, Pattern Recognition, Fuzzy Analysis, Simulation, Behavioral Models (Interdisciplinary Systems Research Ser.)
by Hartmut BosselModels and simulations of all kinds are tools for dealing with reality. Humans have always used mental models to better understand the world around them: to make plans, to consider different possibilities, to share ideas with others, to test changes, and to determine whether or not the development of an idea is feasible. The book Modeling and Simulation uses exactly the same approach except that the traditional mental model is translated into a computer model, and the simulations of alternative outcomes under varying conditions are programmed on the computer. The advantage of this method is that the computer can track the multitude of implications and consequences in complex relationships much more quickly and reliably than the human mind. This unique interdisciplinary text not only provides a self contained and complete guide to the methods and mathematical background of modeling and simulation software (SIMPAS) and a collection of 50 systems models on an accompanying diskette. Students from fields as diverse as ecology and economics will find this clear interactive package an instructive and engaging guide.
Modeling and Simulation
by Hans-Joachim Bungartz Stefan Zimmer Martin Buchholz Dirk PflügerDie Autoren führen auf anschauliche und systematische Weise in die mathematische und informatische Modellierung sowie in die Simulation als universelle Methodik ein. Es geht um Klassen von Modellen und um die Vielfalt an Beschreibungsarten. Aber es geht immer auch darum, wie aus Modellen konkrete Simulationsergebnisse gewonnen werden können. Nach einem kompakten Repetitorium zum benötigten mathematischen Apparat wird das Konzept anhand von Szenarien u. a. aus den Bereichen ,,Spielen - entscheiden - planen" und ,,Physik im Rechner" umgesetzt.
Modeling and Simulation in Python: An Introduction for Scientists and Engineers
by Allen B. DowneyModeling and Simulation in Python teaches readers how to analyze real-world scenarios using the Python programming language, requiring no more than a background in high school math.Modeling and Simulation in Python is a thorough but easy-to-follow introduction to physical modeling—that is, the art of describing and simulating real-world systems. Readers are guided through modeling things like world population growth, infectious disease, bungee jumping, baseball flight trajectories, celestial mechanics, and more while simultaneously developing a strong understanding of fundamental programming concepts like loops, vectors, and functions.Clear and concise, with a focus on learning by doing, the author spares the reader abstract, theoretical complexities and gets right to hands-on examples that show how to produce useful models and simulations.
Modeling and Simulation in Python
by Jason M. KinserThe use of Python as a powerful computational tool is expanding with great strides. Python is a language which is easy to use, and the libraries of tools provides it with efficient versatility. As the tools continue to expand, users can create insightful models and simulations. While the tools offer an easy method to create a pipeline, such constructions are not guaranteed to provide correct results. A lot of things can go wrong when building a simulation - deviously so. Users need to understand more than just how to build a process pipeline. Modeling and Simulation in Python introduces fundamental computational modeling techniques that are used in a variety of science and engineering disciplines. It emphasizes algorithmic thinking skills using different computational environments, and includes a number of interesting examples, including Shakespeare, movie databases, virus spread, and Chess. Key Features: Several theories and applications are provided, each with working Python scripts. All Python functions written for this book are archived on GitHub. Readers do not have to be Python experts, but a working knowledge of the language is required. Students who want to know more about the foundations of modeling and simulation will find this an educational and foundational resource.
Modeling and Simulation of Complex Collective Systems
by Jarosław WąsProviding a comprehensive overview of the modeling of complex systems, with particular emphasis on the collective aspects of these systems, this book situates itself at the forefront of available literature. Exemplifying practically Wolfram’s theses found in A New Kind of Science, discussions center on where it is best to use a cellular automaton, when it is reasonable to use a hybrid approach, and when it is best to use a traditional method such as one based on differential equations. A range of fascinating examples are discussed, ranging from models of crowd dynamics, car traffic, downhill skiers and oil spreading across the sea surface. All are discussed and illustrated with comments. These examples explore how simple rules can create incredibly complex patterns and are used to compare cellular automata with more traditional methods. This book is of critical importance to students and lecturers interested in complex system modeling as well as containing translatable techniques that have applications in a wide range of fields
Modeling and Simulation of Complex Dynamical Systems: Virtual Laboratory Approach based on Wolfram SystemModeler
by Vladimir Ryzhov Tatiana Fedorova Kirill Safronov Shaharin Anwar Sulaiman Mark Ovinis Veeradasan PerumalThis book highlights the practical aspects of computer modelling and simulation of complex dynamical systems for students. Mechanical systems are considered in the book as representative examples of dynamical systems. Wolfram SystemModeler, in combination with Learning Management System Sakai, is used as an instrument for studying features of various physical and technical phenomena and processes. Each of the presented virtual labs may be considered a stand-alone mini project to enable students to go through all the steps of mathematical modelling and computer simulation—from the problem statement to mathematical and physical analysis of the obtained result. The book is useful for teachers to organize the educational process, allowing gradual monitoring of the learning process and assessment of students’ competencies. It also allows tutors to design individual educational trajectories for students to achieve educational properties. The subject of the book is an extension of activity started by the international team of authors within the InMotion project of the European programme ERASMUS+.
Modeling and Simulation of Invasive Applications and Architectures (Computer Architecture and Design Methodologies)
by Sascha Roloff Frank Hannig Jürgen TeichThis book covers two main topics: First, novel fast and flexible simulation techniques for modern heterogeneous NoC-based multi-core architectures. These are implemented in the full-system simulator called InvadeSIM and designed to study the dynamic behavior of hundreds of parallel application programs running on such architectures while competing for resources. Second, a novel actor-oriented programming library called ActorX10, which allows to formally model parallel streaming applications by actor graphs and to analyze predictable execution behavior as part of so-called hybrid mapping approaches, which are used to guarantee real-time requirements of such applications at design time independent from dynamic workloads by a combination of static analysis and dynamic embedding.
Modeling and Simulation of Social-Behavioral Phenomena in Creative Societies: Second International Conference, MSBC 2022, Vilnius, Lithuania, September 21–23, 2022, Proceedings (Communications in Computer and Information Science #1717)
by Nitin Agarwal George B. Kleiner Leonidas SakalauskasThis book constitutes the joint refereed proceedings of the Second International Conference on Modeling and Simulation of Social-Behavioral Phenomena in Creative Societies, MSBC 2022, held in Vilnius, Lithuania, in September 2022.The 14 full papers and 1 short paper presented were carefully reviewed and selected from 35 submissions. The papers are organized in the following topical sections: simulation of behavioral processes; modeling of sustainability; and data science and modeling.
Modeling and Simulation of Social-Behavioral Phenomena in Creative Societies: Third International Conference, MSBC 2024, Almaty, Kazakhstan, September 18–20, 2024, Proceedings (Communications in Computer and Information Science #2211)
by Nitin Agarwal Leonidas Sakalauskas Ualsher TukeyevThis book constitutes the refereed proceedings of the Third International Conference on Modeling and Simulation of Social-Behavioral Phenomena in Creative Societies, MSBC 2024, held in Almaty, Kazakhstan, in September 2024. The 16 full papers presented here were carefully reviewed and selected from 42 submissions. These papers have been categorized under the following topical sections: Computational intelligence and game theory in social sciences; Data analysis and Large language models; Systems approach to economic and social policies modeling.
Modeling and Simulation of Social-Behavioral Phenomena in Creative Societies: First International EURO Mini Conference, MSBC 2019, Vilnius, Lithuania, September 18–20, 2019, Proceedings (Communications in Computer and Information Science #1079)
by Nitin Agarwal Leonidas Sakalauskas Gerhard-Wilhelm WeberThis volume constitutes the proceedings of the First International EURO Mini Conference on Modelling and Simulation of Social-Behavioural Phenomena in Creative Societies, MSBC 2019, held in Vilnius, Lithuania, in September 2019. The 8 full papers and 2 short papers presented were carefully reviewed and selected from 26 submissions. The papers are organized in the following topical sections: computational intelligence in social sciences; modeling and analysis of social-behavioral processes.
Modeling and Simulation with Compose and Activate
by Ramine Nikoukhah Stephen L. CampbellThis book provides a tutorial in the use of Compose and Activate, software packages that provide system modeling and simulation facilities. Advanced system modeling software provide multiple ways of creating models: models can be programmed in specialized languages, graphically constructed as block-diagrams and state machines, or expressed mathematically in equation-based languages. Compose and Activate are introduced in this text in two parts. The first part introduces the multi-language environment of Compose and its use for modeling, simulation and optimization. The second describes the graphical system modeling and optimization with Activate, an open-system environment providing signal-based modeling as well as physical system component-based modeling. Throughout both parts are applied examples from mechanical, biological, and electrical systems, as well as control and signal processing systems. This book will be an invaluable addition with many examples both for those just interested in OML and those doing industrial scale modeling, simulation, and design. All examples are worked using the free basic editions of Activate and Compose that are available.
Modeling and Stability Analysis of Inverter-Based Resources
by Lingling Fan Zhixin MiaoRenewable energy sources interface with the ac grids via inverters and are termed inverter-based resources (IBRs). They are replacing traditional fossil fuel-based synchronous generators at a dazzling speed. In turn, unprecedented dynamic events have occurred, threatening power grid reliability. Modeling and Stability Analysis of Inverter-Based Resources provides a fundamental understanding of IBR dynamics. Developing reliability solutions requires a thorough understanding of challenges, and in this case, IBR-associated dynamics. Modeling and stability analysis play an indispensable role in revealing a mechanism of dynamics. This book covers the essential techniques of dynamic model building for IBRs, including type-3 wind farms, type-4 wind farms, and solar photovoltaics. Besides modeling, this book offers readers the techniques of stability analysis. The text includes three parts. Part 1 concentrates on tools, including electromagnetic transient simulation, analysis, and measurement-based modeling. Part 2 focuses on IBR modeling and analysis details. Part 3 highlights generalized dynamic circuit representation—a unified modeling framework for dynamic and harmonic analysis. This topic of IBR dynamic modeling and stability analysis is interesting, challenging, and intriguing. The authors have led the effort of publishing the 2020 IEEE Power and Energy Society’s TR-80 taskforce report “Wind Energy Systems Subsynchronous Oscillations: Modeling and Events,” and the two taskforce papers on investigation of real-world IBR dynamic events. In this book, the authors share with readers many insights into modeling and analysis for real-world IBR dynamic events investigation.
Modeling and Using Context: 11th International and Interdisciplinary Conference, CONTEXT 2019, Trento, Italy, November 20–22, 2019, Proceedings (Lecture Notes in Computer Science #11939)
by Gábor Bella Paolo BouquetThis book constitutes the proceedings of the 11th International and Interdisciplinary Conference on Modeling and Using Context, CONTEXT 2019, held in Trento, Italy, in November 2019. The 20 full papers and 4 invited talks presented were carefully reviewed and selected from 31 submissions. The papers feature research in a wide range of disciplines related to issues of context and contextual knowledge and discuss commonalities across and differences between the disciplines' approaches to the study of context. They cover a large spectrum of fields, including philosophy of language and of science, computational papers on context-aware information systems, artificial intelligence, and computational linguistics, as well as cognitive and social sciences.