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Modelling and Optimization of Wave Energy Converters
Wave energy offers a promising renewable energy source, however, technologies converting wave energy into useful electricity face many design challenges. This guide presents numerical modelling and optimization methods for the development of wave energy converter technologies, from principles to applications. It covers the development status and perspectives of wave energy converter systems; the fundamental theories on wave power absorption; the modern wave energy converter concepts including oscillating bodies in single and multiple degree of freedom and oscillating water column technologies; and the relatively hitherto unexplored topic of wave energy harvesting farms. It can be used as a specialist student textbook as well as a reference book for the design of wave energy harvesting systems, across a broad range of disciplines, including renewable energy, marine engineering, infrastructure engineering, hydrodynamics, ocean science, and mechatronics engineering.The Open Access version of this book, available at www.routledge.com has been made available under a Creative Commons Attribution-Non Commercial-No Derivatives 4.0 license.
R 2,491.00
Handbook of Optimization in the Railway Industry
This book promotes the use of mathematical optimization and operations research methods in rail transportation. The editors assembled thirteen contributions from leading scholars to present a unified voice, standardize terminology, and assess the state-of-the-art.There are three main clusters of articles, corresponding to the classical stages of the planning process: strategic, tactical, and operational. These three clusters are further subdivided into five parts which correspond to the main phases of the railway network planning process: network assessment, capacity planning, timetabling, resource planning, and operational planning. Individual chapters cover:SimulationCapacity AssessmentNetwork DesignTrain RoutingRobust TimetablingEvent SchedulingTrack AllocationBlockingShuntingRolling StockCrew SchedulingDispatching Delay Propagation
R 8,451.85
Modeling and Optimization of Solar Thermal Systems
In recent years, scientists and researchers have been continually searching for efficient and effective ways to harness solar energy for heat and power production. The development of solar technologies and thermal systems are a prevalent area of study, as they represent a vital step in fully optimizing the potential of solar energy. Unfortunately, research is still lacking on the development and application of these solar thermal systems. Modeling and Optimization of Solar Thermal Systems: Emerging Research and Opportunities provides emerging research exploring the theoretical and practical aspects of optimizing the performance of solar thermal technologies using multicriteria decision-making techniques. Featuring coverage on a broad range of topics such as parabolic trough collectors, hybrid solar energy, and thermal technology, this book is ideally designed for practitioners, engineers, academicians, researchers, students, industry professionals, and educators seeking current research on modern modeling methods of solar thermal systems.
R 5,990.29
Hierarchical Bayesian Optimization Algorithm
This book provides a framework for the design of competent optimization techniques by combining advanced evolutionary algorithms with state-of-the-art machine learning techniques. The primary focus of the book is on two algorithms that replace traditional variation operators of evolutionary algorithms, by learning and sampling Bayesian networks: the Bayesian optimization algorithm (BOA) and the hierarchical BOA (hBOA). They provide a scalable solution to a broad class of problems. The book provides an overview of evolutionary algorithms that use probabilistic models to guide their search, motivates and describes BOA and hBOA in a way accessible to a wide audience, and presents numerous results confirming that they are revolutionary approaches to black-box optimization.
R 2,015.00
Modeling, Simulation and Optimization of Complex Processes
This proceedings volume contains a selection of papers presented at the symposium "International Conference on High Performance Scientific Computing'' held at the Hanoi Institute of Mathematics of the Vietnam National Center for Natural Science and Technology (NCST), March 10-14, 2003. The conference has been organized by the Hanoi Institute of Mathematics, SFB 359 ''Reactive Flows, Transport and Diffusion'', Heidelberg, Ho Chi Minh City University of Technology and Interdisciplinary Center for Scientific Computing (IWR), Heidelberg. The contributions cover the broad interdisciplinary spectrum of scientific computing and present recent advances in theory, development of methods, and applications in practice. Subjects covered are mathematical modelling, numerical simulation, methods for optimization and optimal control, parallel computing, symbolic computing, software development, applications of scientific computing in physics, chemistry, biology and mechanics, environmental and hydrology problems, transport, logistics and site location, communication networks, production scheduling, industrial and commercial problems.
R 6,683.26
Dynamic Econometrics For Empirical Macroeconomic Modelling
For Masters and PhD students in EconomicsIn this textbook, the duality between the equilibrium concept used in dynamic economic theory and the stationarity of economic variables is explained and used in the presentation of single equations models and system of equations such as VARs, recursive models and simultaneous equations models.The book also contains chapters on: exogeneity, in the context of estimation, policy analysis and forecasting; automatic (computer based) variable selection, and how it can aid in the specification of an empirical macroeconomic model; and finally, on a common framework for model-based economic forecasting.Supplementary materials and notes are available on the publisher's website.
R 2,601.83
Modeling, Simulation, and Optimization
This book features selected contributions in the areas of modeling, simulation, and optimization. The contributors discusses requirements in problem solving for modeling, simulation, and optimization. Modeling, simulation, and optimization have increased in demand in exponential ways and how potential solutions might be reached. They describe how new technologies in computing and engineering have reduced the dimension of data coverage worldwide, and how recent inventions in information and communication technology (ICT) have inched towards reducing the gaps and coverage of domains globally. The chapters cover how the digging of information in a large data and soft-computing techniques have contributed to a strength in prediction and analysis, for decision making in computer science, technology, management, social computing, green computing, and telecom. The book provides an insightful reference to the researchers in the fields of engineering and computer science. Researchers, academics, and professionals will benefit from this volume.Features selected expanded papers in modeling, simulation, and optimization from COMPSE 2016;Includes research into soft computing and its application in engineering and technology;Presents contributions from global experts in academia and industry in modeling, simulation, and optimization.
R 4,542.58
Conceptual Shape Optimization of Entry Vehicles
This book covers the parameterization of entry capsules, including Apollo capsules and planetary probes, and winged entry vehicles such as the Space Shuttle and lifting bodies. The aerodynamic modelling is based on a variety of panel methods that take shadowing into account, and it has been validated with flight and wind tunnel data of Apollo and the Space Shuttle. The shape optimization is combined with constrained trajectory analysis, and the multi-objective approach provides the engineer with a Pareto front of optimal shapes. The method detailed in Conceptual Shape Optimization of Entry Vehicles is straightforward, and the output gives the engineer insight in the effect of shape variations on trajectory performance. All applied models and algorithms used are explained in detail, allowing for reconstructing the design tool to the researcher’s requirements. Conceptual Shape Optimization of Entry Vehicles will be of interest to both researchers and graduate students in the field of aerospace engineering, and to practitioners within the aerospace industry.
R 5,861.00
Mathematical Modelling in Real Life Problems
This book is intended to be a useful contribution for the modern teaching of applied mathematics, educating Industrial Mathematicians that will meet the growing demand for such experts. It covers many applications where mathematics play a fundamental role, from biology, telecommunications, medicine, physics, finance and industry. It is presented in such a way that can be useful in Modelation, Simulation and Optimization courses, targeting master and PhD students. Its content is based on many editions from the successful series of Modelling Weeks organized by the European Consortium of Mathematics in Industry (ECMI). Each chapter addresses a particular problem, and is written in a didactic way, providing the description of the problem, the particular way of approaching it and the proposed solution, along with the results obtained.
R 4,624.71
Aggregation in Large-Scale Optimization
When analyzing systems with a large number of parameters, the dimen sion of the original system may present insurmountable difficulties for the analysis. It may then be convenient to reformulate the original system in terms of substantially fewer aggregated variables, or macrovariables. In other words, an original system with an n-dimensional vector of states is reformulated as a system with a vector of dimension much less than n. The aggregated variables are either readily defined and processed, or the aggregated system may be considered as an approximate model for the orig inal system. In the latter case, the operation of the original system can be exhaustively analyzed within the framework of the aggregated model, and one faces the problems of defining the rules for introducing macrovariables, specifying loss of information and accuracy, recovering original variables from aggregates, etc. We consider also in detail the so-called iterative aggregation approach. It constructs an iterative process, at· every step of which a macroproblem is solved that is simpler than the original problem because of its lower dimension. Aggregation weights are then updated, and the procedure passes to the next step. Macrovariables are commonly used in coordinating problems of hierarchical optimization.
R 3,038.50
Modeling, Control and Optimization of Complex Systems
Modeling, Control And Optimization Of Complex Systems is a collection of contributions from leading international researchers in the fields of dynamic systems, control theory, and modeling. These papers were presented at the Symposium on Modeling and Optimization of Complex Systems in honor of Larry Yu-Chi Ho in June 2001. They include exciting research topics such as: -modeling of complex systems, -power control in ad hoc wireless networks, -adaptive control using multiple models, -constrained control, -linear quadratic control, -discrete events, -Markov decision processes and reinforcement learning, -optimal control for discrete event and hybrid systems, -optimal representation and visualization of multivariate data and functions in low-dimensional spaces.
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Large Scale Optimization
On February 15-17, 1993, a conference on Large Scale Optimization, hosted by the Center for Applied Optimization, was held at the University of Florida. The con ference was supported by the National Science Foundation, the U. S. Army Research Office, and the University of Florida, with endorsements from SIAM, MPS, ORSA and IMACS. Forty one invited speakers presented papers on mathematical program ming and optimal control topics with an emphasis on algorithm development, real world applications and numerical results. Participants from Canada, Japan, Sweden, The Netherlands, Germany, Belgium, Greece, and Denmark gave the meeting an important international component. At tendees also included representatives from IBM, American Airlines, US Air, United Parcel Serice, AT & T Bell Labs, Thinking Machines, Army High Performance Com puting Research Center, and Argonne National Laboratory. In addition, the NSF sponsored attendance of thirteen graduate students from universities in the United States and abroad. Accurate modeling of scientific problems often leads to the formulation of large scale optimization problems involving thousands of continuous and/or discrete vari ables. Large scale optimization has seen a dramatic increase in activities in the past decade. This has been a natural consequence of new algorithmic developments and of the increased power of computers. For example, decomposition ideas proposed by G. Dantzig and P. Wolfe in the 1960's, are now implement able in distributed process ing systems, and today many optimization codes have been implemented on parallel machines.
R 6,029.63
Modeling and Optimization of Food and Bio-Processes
Models have become an indispensable tool for scientists and engineers alike. For the scientist, a model makes it possible to quantitatively test hypotheses, understand phenomena, and, if necessary, revise them until a satisfactory agreement with experiments is reached. For the engineer, a technical object is nowadays designed, tested and optimized in simulation long before its physical birth. In all cases, modeling is an important gas pedal of research and engineering, and a tool for competitiveness in the modern world. Modeling and Optimization of Food and Bio-Processes is aimed at anyone with a grounding in process, chemical or microbiological engineering, as well as students of these disciplines. Drawing on the authors’ extensive teaching and research experience, this book is designed to teach engineers and scientists the main concepts and the right reflexes to adopt when embarking on the noble art of modeling.
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Multilevel Optimization: Algorithms and Applications
Researchers working with nonlinear programming often claim "the word is non linear" indicating that real applications require nonlinear modeling. The same is true for other areas such as multi-objective programming (there are always several goals in a real application), stochastic programming (all data is uncer tain and therefore stochastic models should be used), and so forth. In this spirit we claim: The word is multilevel. In many decision processes there is a hierarchy of decision makers, and decisions are made at different levels in this hierarchy. One way to handle such hierar chies is to focus on one level and include other levels' behaviors as assumptions. Multilevel programming is the research area that focuses on the whole hierar chy structure. In terms of modeling, the constraint domain associated with a multilevel programming problem is implicitly determined by a series of opti mization problems which must be solved in a predetermined sequence. If only two levels are considered, we have one leader (associated with the upper level) and one follower (associated with the lower level).
R 6,019.21
Power System Optimization Modeling in GAMS
This unique book describes how the General Algebraic Modeling System (GAMS) can be used to solve various power system operation and planning optimization problems. This book is the first of its kind to provide readers with a comprehensive reference that includes the solution codes for basic/advanced power system optimization problems in GAMS, a computationally efficient tool for analyzing optimization problems in power and energy systems. The book covers theoretical background as well as the application examples and test case studies. It is a suitable reference for dedicated and general audiences including power system professionals as well as researchers and developers from the energy sector and electrical power engineering community and will be helpful to undergraduate and graduate students.
R 8,387.99
Modelling with Ordinary Differential Equations
Modelling with Ordinary Differential Equations integrates standard material from an elementary course on ordinary differential equations with the skills of mathematical modeling in a number of diverse real-world situations. Each situation highlights a different aspect of the theory or modeling. Carefully selected exercises and projects present excellent opportunities for tutorial sessions and self-study.This text/reference addresses common types of first order ordinary differential equations and the basic theory of linear second order equations with constant coefficients. It also explores the elementary theory of systems of differential equations, Laplace transforms, and numerical solutions. Theorems on the existence and uniqueness of solutions are a central feature. Topics such as curve fitting, time-delay equations, and phase plane diagrams are introduced. The book includes algorithms for computer programs as an integral part of the answer-finding process. Professionals and students in the social and biological sciences, as well as those in physics and mathematics will find this text/reference indispensable for self-study.
R 5,331.07
Modelling and Identification in Robotics
As the use and relevance of robotics for countless scientific purposes grows all the time, research into the many diverse elements of the subject becomes ever more important and in demand. This volume examines in depth the most topical, complex issues of modelling and identification in robotics. The book is divided into three main parts. The !first part is devoted to robot dynamics modelling and identification of robot and load parameters, incorporating friction torques, discussing identification schemes, and presenting simulations and experiment al results of robot and load dynamic parameters identification. A general concept of robot programming language for research and educational purposes is examined and there is a detailed outline of its basic structures along with hardware requirements, which both constitute an open robot controller architecture. Finally a hybrid controller is derived, and several experimental results of this system are outlined. This impressive discussion of the topic covers both the theoretical and practical, illustrated throughout by examples and experimental results, and will be of value to anyone researching or practising within the field of robotics, automation and system i dentification or to control engineers.
R 3,036.44
Computing Methods in Optimization Problems
This volume is based on papers presented at the 2nd International Conference on Computing Methods in Optimization Problems held in San Remo, Italy, September 9-13, 1968. The Conference was sponsored by the Society of Industrial and Applied Mathematicians (SIAM), with the cooperation of the University of California and the Univer- sity of California and the University of Southern Califor- nia. The Conference focussed on recent advances in com- putational methods for optimization problems in diverse areas including: Computational Aspects of Optimal Control and Trajec- tory Problems; Computational Techniques in Mathematical Programming; Computational Techniques in Optimization Problems in Economics, Metero1ogy, Biomedicine and Related Areas; Identification and Inverse Problems; Computational Aspects of Decoding and Information Retrieval Problems; Pattern Recognition Problems. The Organizing Committee of the Conference consisted of: A. V. Balakrishnan (U. S. A. ) - Chairman L. W. Neustadt (U. S. A. ) - Co-Chairman L. A. Zadeh (U. S. A. ) - Co-Chairman G. Debreu (U. S. A. ) E. Gilbert (U. S. A. ) H. Kelley (U. S. A. ) J. Rosen (U. S. A. ) J. Lions (France) A. Ruberti (Italy) A.Lepschy (Italy) E. Biondi (Italy) G. Marchuk (U. S. S. R. ) N. Moiseev (U. S. S. R. ) B. Pschenichniy (U. S. S. R. ) The Conference was hosted by the Consiglio Naziona1e Delle Ricerche, Italy. CONTENTS G. Arienti and A. Colonelli Daneri: Computation of the Switching Times in Optimal Control Problems of Bang-Bang Type ******************** 1 M.
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Modelling and Simulation
This hands-on textbook/reference presents an introduction to the fundamental aspects of modelling and simulation, both for those wishing to learn about this methodology and also for those who have a need to apply it in their work. The text is supported by illustrative examples, drawn from projects formulated within the domains of discrete-event dynamic systems (DEDS) and continuous-time dynamic systems (CTDS).This updated new edition has been enhanced with new illustrative case studies, and additional examples demonstrating some new features and the effectiveness of the ABCmod conceptual modelling framework. Changes that facilitate the development of simulation models with ABSmod/J are illustrated. New material includes a presentation of the experimentation strategy called “design of experiments” and three new chapters that explore the optimization-simulation interface.Topics and features: presents a goal-based and project-oriented perspective of modelling and simulation; describes the ABCmod framework, an activity-based conceptual modelling framework for DEDS; examines the simulation-optimization interface in both the CTDS and DEDS domains; provides numerous illustrative examples, case studies and useful algorithms, as well as exercises and projects at the end of most chapters; includes appendices on probability and statistics, the GPSS programming environment, and relevant MATLAB features; provides supplementary software and teaching support material at an associated website, including lecture slides and a methodology for organizing student projects.Serving as an essential guide to the foundations of modelling and simulation, this practical primer is ideal for senior undergraduate and junior graduate-level students. Also suitable for self-study, the book will be of great benefit to professionals seeking insight into the vast potential of this rapidly evolving problem-solving paradigm.
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Optimization
Optimization: 100 Examples is a book devoted to the analysis of scenarios for which the use of well-known optimization methods encounter certain difficulties. Analysing such examples allows a deeper understanding of the features of these optimization methods, including the limits of their applicability. In this way, the book seeks to stimulate further development and understanding of the theory of optimal control. The study of the presented examples makes it possible to more effectively diagnose problems that arise in the practical solution of optimal control problems, and to find ways to overcome the difficulties that have arisen. FeaturesVast collection of examplesSimple. accessible presentationSuitable as a research reference for anyone with an interest in optimization and optimal control theory, including mathematicians and engineersExamples differ in properties, i.e. each effect for each class of problems is illustrated by a unique example.
R 11,239.50
Modelling and Optimization of Distributed Parameter Systems Applications to engineering
This volume contains a selection of papers presented at the conference on Modelling and Optimization of Distributed Parameter Systems with Applications to Engineering, held in Warsaw on July 17-21, 1995. This conference was a consecutive one in the series of conferences sponsored by the IFIP Working Group WG 7.2 "Computational Techniques in Distributed Systems", chaired by Irena Lasiecka. It was organized by the Systems Research Institute of the Polish Academy of Sciences and supported financially by the following institutions: -European Community on Computational Methods in Applied Sciences, -Fundacja Stefana Batorego, -International Mathematical Union, - Telekomunikacja Polska S.A. The following scientists took an active part in preparation of the scientific program of the conference, organizing or helping to organize special sessions: - E. Casas and I.Lasiecka (Optimization and Optimal ControQ, Z.Mr6z (Mechanical Applications), - M.Niezg6dka (Properties of Solutions to P.D.E.s), - L.Pandolfi (Hamilton and Riccati Equation Approaches to Optimization), - K.Sobczyk and J.Zabczyk (Stochastic Systems), - J.Sokolowski and J.-P.Zolesio (Shape Optimization), - J.Wa8niewski (Scientific Computation).In the conference participated 133 scientists from 22 countries. Ten invited plenary lectures and 103 contributed papers have been presented. This volume contains a part of the presented material. The core of it is constituted by papers devoted to control and optimization of distributed parameter systems. Other selection will be included in a special issue of the quarterly Control & Cybernetics to be published in 1996.
R 6,016.56
Modeling, Simulation and Optimization of Bipedal Walking
The model-based investigation of motions of anthropomorphic systems is an important interdisciplinary research topic involving specialists from many fields such as Robotics, Biomechanics, Physiology, Orthopedics, Psychology, Neurosciences, Sports, Computer Graphics and Applied Mathematics. This book presents a study of basic locomotion forms such as walking and running is of particular interest due to the high demand on dynamic coordination, actuator efficiency and balance control. Mathematical models and numerical simulation and optimization techniques are explained, in combination with experimental data, which can help to better understand the basic underlying mechanisms of these motions and to improve them. Example topics treated in this book areModeling techniques for anthropomorphic bipedal walking systemsOptimized walking motions for different objective functionsIdentification of objective functions from measurementsSimulation and optimization approaches for humanoid robotsBiologically inspired control algorithms for bipedal walkingGeneration and deformation of natural walking in computer graphicsImitation of human motions on humanoidsEmotional body language during walking Simulation of biologically inspired actuators for bipedal walking machinesModeling and simulation techniques for the development of prosthesesFunctional electrical stimulation of walking.
R 3,672.80
Advances in Multilevel Modeling for Educational Research
The significance that practitioners are placing on the use of multilevel models is undeniable as researchers want to both accurately partition variance stemming from complex sampling designs and understand relations within and between variables describing the hierarchical levels of these nested data structures. Simply scan the applied literature and one can see evidence of this trend by noticing the number of articles adopting multilevel models as their primary modeling framework. Helping to drive the popularity of their use, governmental funding agencies continue to advocate the use of multilevel models as part of a comprehensive analytic strategy for conducting rigorous and relevant research to improve our nation’s education system.Advances in Multilevel Modeling for Educational Research: Addressing Practical Issues Found in Real?World Applications is a resource intended for advanced graduate students, faculty and/or researchers interested in multilevel data analysis, especially in education, social and behavioral sciences. The chapters are written by prominent methodological researchers across diverse research domains such as educational statistics, quantitative psychology, and psychometrics. Each chapter exposes the reader to some of the latest methodological innovations, refinements and state?of?the?art developments and perspectives in the analysis of multilevel data including current best practices of standard techniques.We believe this volume will be particularly appealing to researchers in domains including but not limited to: educational policy and administration, educational psychology including school psychology and special education, and clinical psychology. In fact, we believe this volume will be a desirable resource for any research area that uses hierarchically nested data. The book will likely be attractive to applied and methodological researchers in several professional organizations such as the American Educational Research Association (AERA), the American Psychological Association (APA), the American Psychological Society (APS), the Society for Research on Educational Effectiveness (SREE), and other related organizations.
R 4,739.72
Engineering Optimization
The classic introduction to engineering optimization theory and practice--now expanded and updated Engineering optimization helps engineers zero in on the most effective, efficient solutions to problems. This text provides a practical, real-world understanding of engineering optimization. Rather than belaboring underlying proofs and mathematical derivations, it emphasizes optimization methodology, focusing on techniques and stratagems relevant to engineering applications in design, operations, and analysis. It surveys diverse optimization methods, ranging from those applicable to the minimization of a single-variable function to those most suitable for large-scale, nonlinear constrained problems. New material covered includes the duality theory, interior point methods for solving LP problems, the generalized Lagrange multiplier method and generalization of convex functions, and goal programming for solving multi-objective optimization problems. A practical, hands-on reference and text, Engineering Optimization, Second Edition covers: * Practical issues, such as model formulation, implementation, starting point generation, and more * Current, state-of-the-art optimization software * Three engineering case studies plus numerous examples from chemical, industrial, and mechanical engineering * Both classical methods and new techniques, such as successive quadratic programming, interior point methods, and goal programming Excellent for self-study and as a reference for engineering professionals, this Second Edition is also ideal for senior and graduate courses on engineering optimization, including television and online instruction, as well as for in-plant training.
R 6,218.00
Portfolio Selection Using Multi-Objective Optimisation
This book explores the risk-return paradox in portfolio selection by incorporating multi-objective criteria. Empirical research is presented on the development of alternate portfolio models and their relative performance in the risk/return framework to provide solutions to multi-objective optimization. Next to outlining techniques for undertaking individual investor’s profiling and portfolio programming, it also offers a new and practical approach for multi-objective portfolio optimization. This book will be of interest to Foreign Institutional Investors (FIIs), Mutual Funds, investors, and researchers and students in the field.
R 5,027.12
Iterative Methods in Combinatorial Optimization
With the advent of approximation algorithms for NP-hard combinatorial optimization problems, several techniques from exact optimization such as the primal-dual method have proven their staying power and versatility. This book describes a simple and powerful method that is iterative in essence and similarly useful in a variety of settings for exact and approximate optimization. The authors highlight the commonality and uses of this method to prove a variety of classical polyhedral results on matchings, trees, matroids and flows. The presentation style is elementary enough to be accessible to anyone with exposure to basic linear algebra and graph theory, making the book suitable for introductory courses in combinatorial optimization at the upper undergraduate and beginning graduate levels. Discussions of advanced applications illustrate their potential for future application in research in approximation algorithms.
R 4,328.50
System Modeling and Optimization
This book presents selected proceedings from the 22nd biennial IFIP conference on System Modeling and Optimization, held in Turin, Italy in July of 2005. This edition of the conference is dedicated to the achievements of Camillo Possio, who was killed sixty years ago during the last air raid over Turin. For more information about the 300 other books in the IFIP series, please visit www.springeronline.com.
R 3,039.51
Project Optimization
A comprehensive and easy to understand introduction to a wide range of tools to help designers to optimize their projects. The authors are engineers and therefore many of the examples are on engineering applications, but the techniques presented are common to various areas of knowledge and pervade disciplinary divisions. The book describes the fundamental ideas, mathematical and graphic methods and shows how to use Matlab and EXCEL for optimization.
R 1,710.00
Decision Tree and Ensemble Learning Based on Ant Colony Optimization
This book not only discusses the important topics in the area of machine learning and combinatorial optimization, it also combines them into one. This was decisive for choosing the material to be included in the book and determining its order of presentation.Decision trees are a popular method of classification as well as of knowledge representation. At the same time, they are easy to implement as the building blocks of an ensemble of classifiers. Admittedly, however, the task of constructing a near-optimal decision tree is a very complex process.The good results typically achieved by the ant colony optimization algorithms when dealing with combinatorial optimization problems suggest the possibility of also using that approach for effectively constructing decision trees. The underlying rationale is that both problem classes can be presented as graphs. This fact leads to option of considering a larger spectrum of solutions than those based on the heuristic. Moreover, ant colony optimization algorithms can be used to advantage when building ensembles of classifiers.This book is a combination of a research monograph and a textbook. It can be used in graduate courses, but is also of interest to researchers, both specialists in machine learning and those applying machine learning methods to cope with problems from any field of R&D.
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Convex Analysis for Optimization
This textbook offers graduate students a concise introduction to the classic notions of convex optimization. Written in a highly accessible style and including numerous examples and illustrations, it presents everything readers need to know about convexity and convex optimization.The book introduces a systematic three-step method for doing everything, which can be summarized as "conify, work, deconify". It starts with the concept of convex sets, their primal description, constructions, topological properties and dual description, and then moves on to convex functions and the fundamental principles of convex optimization and their use in the complete analysis of convex optimization problems by means of a systematic four-step method. Lastly, it includes chapters on alternative formulations of optimality conditions and on illustrations of their use."The author deals with the delicate subjects in a precise yet light-minded spirit... For experts in the field, this book not only offers a unifying view, but also opens a door to new discoveries in convexity and optimization...perfectly suited for classroom teaching." Shuzhong Zhang, Professor of Industrial and Systems Engineering, University of Minnesota
R 2,497.35
Machine Learning Hybridization and Optimization for Intelligent Applications
This book discusses state-of-the-art reviews of the existing machine learning techniques and algorithms including hybridizations and optimizations. It covers applications of machine learning via artificial intelligence (AI) prediction tools, discovery of drugs, neuroscience, diagnosis in multiple imaging modalities, pattern recognition approaches to functional magnetic resonance imaging, image and speech recognition, automatic language translation, medical diagnostic, stock market prediction, traffic prediction, and product automation.Features:Focuses on hybridization and optimization of machine learning techniquesReviews supervised, unsupervised, and reinforcement learning using case study-based applicationsCovers the latest machine learning applications in as diverse domains as the Internet of Things, data science, cloud computing, and distributed and parallel computingExplains computing models using real-world examples and dataset-based experimentsIncludes case study-based explanations and usage for machine learning technologies and applicationsThis book is aimed at graduate students and researchers in machine learning, artificial intelligence, and electrical engineering.
R 3,114.00
Operations Management and Data Analytics Modelling
Operations Management and Data Analytics Modelling: Economic Crises Perspective addresses real operation management problems in thrust areas like the healthcare and energy management sectors and Industry 4.0.It discusses recent advances and trends in developing data-driven operation management-based methodologies, big data analysis, application of computers in industrial engineering, optimization techniques, development of decision support systems for industrial operation, the role of a multiple-criteria decision-making (MCDM) approach in operation management, fuzzy set theory-based operation management modelling and Lean Six Sigma.Features Discusses the importance of data analytics in industrial operations to improve economy Provides step-by-step implementation of operation management models to identify best practices Covers in-depth analysis using data-based operation management tools and techniques Discusses mathematical modelling for novel operation management models to solve industrial problemsThis book is aimed at graduate students and professionals in the field of industrial and production engineering, mechanical engineering and materials science.
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Applied Simulation and Optimization 2
Building on the author’s earlier Applied Simulation and Optimization, this book presents novel methods for solving problems in industry, based on hybrid simulation-optimization approaches that combine the advantages of both paradigms. The book serves as a comprehensive guide to tackling scheduling, routing problems, resource allocations and other issues in industrial environments, the service industry, production processes, or supply chains and aviation. Logistics, manufacturing and operational problems can either be modelled using optimization techniques or approaches based on simulation methodologies. Optimization techniques have the advantage of performing efficiently when the problems are properly defined, but they are often developed through rigid representations that do not include or accurately represent the stochasticity inherent in real systems. Furthermore, important information is lost during the abstraction process to fit each problem into the optimization technique. On the other hand, simulation approaches possess high description levels, but the optimization is generally performed through sampling of all the possible configurations of the system. The methods explored in this book are of use to researchers and practising engineers in fields ranging from supply chains to the aviation industry.
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Optimization and Operations Research
This volume constitutes the proceedings of the workshop "Optimierung und Operations Research", held at the Elly Holterhoff Backing Stift (Bad Honnef) of the University of Bonn, October 2-8, 1977. This conference was devoted to recent advances in the field of mathe- matical programming, optimization techniques, and operations research. It was attended by about 50 invited participants. Furthermore many scholars in these areas showed a great interest in this workshop, despite several other conferences and activities on similar topics in the year 1977. The organizers regret that considerations of avail- able space for conference activities limited the number of participants. This widespread interest, the high quality of the lectures presented and the active and stimulating discussions at the conference mani- fested the breadth of the activity ongoing in the field covered by this workshop and the necessity that this field be cultivated to a greater extent by the scientific community.The workshop was organized by the Institute of Operations Research (Sonderforschungsbereich 21), University of Bonn and was generously sponsored by the Gesellschaft der Freunde und Forderer der Rheinischen Friedrich-Wilhelms-Universitat and by IBM Germany. Only through this invaluable support was this workshop possible; for this the editors wish to express their sincere thanks and appreciation. Bonn, December 1977 R. Henn B. Korte W. Oettli III TABLE OF CONTENTS A. Bachem The theorem of Minkowski for polyhedral monoids and aggregated linear diophantine systems * * * . * * * * * * * S. Baum and L.E. Trotter, Jr.
R 3,134.64
Separable Optimization
In this book, the theory, methods and applications of separable optimization are considered. Some general results are presented, techniques of approximating the separable problem by linear programming problem, and dynamic programming are also studied. Convex separable programs subject to inequality/ equality constraint(s) and bounds on variables are also studied and convergent iterative algorithms of polynomial complexity are proposed. As an application, these algorithms are used in the implementation of stochastic quasigradient methods to some separable stochastic programs. The problems of numerical approximation of tabulated functions and numerical solution of overdetermined systems of linear algebraic equations and some systems of nonlinear equations are solved by separable convex unconstrained minimization problems. Some properties of the Knapsack polytope are also studied. This second edition includes a substantial amount of new and revised content. Three new chapters, 15-17, are included. Chapters 15-16 are devoted to the further analysis of the Knapsack problem. Chapter 17 is focused on the analysis of a nonlinear transportation problem. Three new Appendices (E-G) are also added to this edition and present technical details that help round out the coverage. Optimization problems and methods for solving the problems considered are interesting not only from the viewpoint of optimization theory, optimization methods and their applications, but also from the viewpoint of other fields of science, especially the artificial intelligence and machine learning fields within computer science. This book is intended for the researcher, practitioner, or engineer who is interested in the detailed treatment of separable programming and wants to take advantage of the latest theoretical and algorithmic results. It may also be used as a textbook for a special topics course or as a supplementary textbook for graduate courses on nonlinear and convex optimization.
R 3,588.00
Stochastic Modeling and Optimization of Manufacturing Systems and Supply Chains
This volume originates from two workshops, both focusing on themes that are reflected in the title of the volume. The first workshop took place at Eindhoven University of Technology, April 24-26, 2001, on the occasion of the University granting a doctorate honoris causa to Profes sor John A. Buzacott. The second workshop was held on June 15, 2002 at Cornell University (preceding the annual INFORMSjMSOM Confer ence), honoring John's retirement and his lifetime contributions. Each of the two workshops consisted of about a dozen technical presentations. The objective of the volume, however, is not to simply publish the proceedings of the two workshops. Rather, our objective is to put to gether a select set of articles, each organized into a well-written chapter, focusing on a timely topic. Collected into a single volume, these chapters aim to serve as a useful reference for researchers and practitioners alike, and also as reading materials for graduate courses or seminars.
R 4,674.43
Optimization, Machine Learning, and Fuzzy Logic: Theory, Algorithms, and Applications
Optimization, machine learning, and fuzzy logic are fundamental in the field of computational intelligence, each contributing to solving complex problems across various domains. Optimization techniques focus on finding the best solutions to problems by improving efficiency and minimizing resources. Machine learning enables systems to learn from data, making predictions or decisions without being programmed. Fuzzy logic deals with uncertainty and imprecision, allowing for flexible decision-making processes. Together, these theories, algorithms, and applications solve challenges in fields such as engineering, finance, and healthcare, where traditional methods often fall short. The continued application and exploration of these disciplines may unveil new possibilities for advanced problem-solving and intelligent systems. Optimization, Machine Learning, and Fuzzy Logic: Theory, Algorithms, and Applications explores optimization techniques, fuzzy logic, and their integration with machine learning. It covers fundamental concepts, mathematical foundations, algorithms, and applications, providing a holistic understanding of these domains. This book covers topics such as disease detection, deep learning, and text analysis, and is a useful resource for engineers, data scientists, medical professionals, academicians, and researchers.
R 11,059.24
Hybrid Methods for Modeling and Optimizing Complex Systems
Delivering innovative methods for addressing complex systems, this book presents the latest advances in hybrid modeling, machine learning, and digital technologies. Based on selected papers from the III International Workshop "Hybrid Methods of Modeling and Optimization in Complex Systems" held December 2-4, 2024, in Krasnoyarsk, Russia, the book covers hybrid modeling and optimization, intelligent data analysis, financial forecasting, industrial and educational digitalization, AI-guided decision support, and digital system security. Readers will find such interdisciplinary applications as climate project modeling, agricultural digital services, and the digital platform economy; e-learning analysis and digital competence development; digital twins and production optimization; as well as research on network systems. It is essential for researchers, practitioners, and educators seeking practical solutions and advanced hybrid methods for diverse scientific and engineering challenges.
R 9,158.00
Multicriteria Optimization and Engineering
method enables readers to: *efficiently design higher-quality, lower cost objects with less metal requirements, vibration and noise, and with lower dynamic loads and energy consumption *determine optimal solutions, regardless of the number of criteria involved, and to identify relationships among different criteria and between criteria and design variables *accurately account for discrepancies between theoretical and actual characteristics, using a special set of adequacy criteria *determine optimal design variables for complex finite element models In addition, the book helps readers: *enhance the potential of the PSI method with theoretical investigations and algorithms for approximating the feasible solutions set and Pareto optimal set *facilitate proficient problem-solving by incorporating recently obtained results from the theory of uniformly distributed sequences *evaluate design procedures by observing examples ranging from machine tools and agricultural equipment to automobiles and aviation This practical, in-depth treatment of multicriteria optimization and engineering is essential for engineers and designers working in research and development of manufacturing machines, mechanisms and structures. It is also an important text for students of applied mathematics, mechanical engineering, optimal control and operations research.
R 3,088.82
Distillation Control, Optimization, and Tuning
Emphasis on improved quality and performance of distilled products and the demand for reduced operating costs place a heavy burden on both the personnel responsible for profitability and the manufacturing department charged with operating the processing equipment. There have been dramatic improvements in the computer software and hardware used to simulate and model the distillation process and potential response to experimentation, but mastering the art of distillation process and control still requires solid understanding of a large body of information.With a focus on achieving product purity at low cost, Distillation Control, Optimization, and Tuning: Fundamentals and Strategies highlights core concepts. These include process variables for continuous binary distillation columns and the four basic control strategies, the distillate and bottoms product quality performance objectives, and the tuning of process control loops. Without dwelling on complex mathematical descriptions, the book presents the fundamentals of process control of a distillation column as a separation and purification unit operation. It covers the concepts and functional criteria that are critical to successful implementation of process control, as well as measurement and improvement of product quality performance. It describes how process control loops for distillation columns can be tuned for stable operation, with a balance between minimum variability from setpoint changes and excellent response to load disturbances. Designed for students, engineers, technicians, and plant operators alike, this book emphasizes the prevailing need to strike a balance between the details of hypotheses and good engineering judgment. The author outlines learning objectives at the beginning of each chapter and includes chapter-end summaries, exercises, and references to help readers acquire essential knowledge and understanding. The result is a resource that will inform future decisions for the design, operation, and troubleshooting of distillation process control systems.
R 12,297.74
Modern Numerical Nonlinear Optimization
This book includes a thorough theoretical and computational analysis of unconstrained and constrained optimization algorithms and combines and integrates the most recent techniques and advanced computational linear algebra methods. Nonlinear optimization methods and techniques have reached their maturity and an abundance of optimization algorithms are available for which both the convergence properties and the numerical performances are known. This clear, friendly, and rigorous exposition discusses the theory behind the nonlinear optimization algorithms for understanding their properties and their convergence, enabling the reader to prove the convergence of his/her own algorithms. It covers cases and computational performances of the most known modern nonlinear optimization algorithms that solve collections of unconstrained and constrained optimization test problems with different structures, complexities, as well as those with large-scale real applications. The book is addressed to all those interested in developing and using new advanced techniques for solving large-scale unconstrained or constrained complex optimization problems. Mathematical programming researchers, theoreticians and practitioners in operations research, practitioners in engineering and industry researchers, as well as graduate students in mathematics, Ph.D. and master in mathematical programming will find plenty of recent information and practical approaches for solving real large-scale optimization problems and applications.
R 7,306.91
