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Optimization in Economic Theory
* This is the new edition of a popular student textbook. The first edition was well-received. The author has made revisions and additions to enhance the book's usefulness without destroying its distinctive character as a lucid, thorough, and readable text. It gives a broad treatment of optimization methods, building on simple economic theory and elementary linear algebra and calculus, and reinforcing each new mathematical idea by relating it to its economicsapplication.
R 3,558.00
Introduction to Polynomial and Semi-Algebraic Optimization
This is the first comprehensive introduction to the powerful moment approach for solving global optimization problems (and some related problems) described by polynomials (and even semi-algebraic functions). In particular, the author explains how to use relatively recent results from real algebraic geometry to provide a systematic numerical scheme for computing the optimal value and global minimizers. Indeed, among other things, powerful positivity certificates from real algebraic geometry allow one to define an appropriate hierarchy of semidefinite (SOS) relaxations or LP relaxations whose optimal values converge to the global minimum. Several extensions to related optimization problems are also described. Graduate students, engineers and researchers entering the field can use this book to understand, experiment with and master this new approach through the simple worked examples provided.
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Sequential Approximate Multiobjective Optimization Using Computational Intelligence
Many kinds of practical problems such as engineering design, industrial m- agement and ?nancial investment have multiple objectives con?icting with eachother. Thoseproblemscanbeformulatedasmultiobjectiveoptimization. In multiobjective optimization, there does not necessarily a unique solution which minimizes (or maximizes) all objective functions. We usually face to the situation in which if we want to improve some of objectives, we have to give up other objectives. Finally, we pay much attention on how much to improve some of objectives and instead how much to give up others. This is called “trade-o?. ” Note that making trade-o? is a problem of value ju- ment of decision makers. One of main themes of multiobjective optimization is how to incorporate value judgment of decision makers into decision s- port systems. There are two major issues in value judgment (1) multiplicity of value judgment and (2) dynamics of value judgment. The multiplicity of value judgment is treated as trade-o? analysis in multiobjective optimi- tion. On the other hand, dynamics of value judgment is di?cult to treat. However, it is natural that decision makers change their value judgment even in decision making process, because they obtain new information during the process. Therefore, decision support systems are to be robust against the change of value judgment of decision makers. To this aim, interactive p- grammingmethodswhichsearchasolutionwhileelicitingpartialinformation on value judgment of decision makers have been developed. Those methods are required to perform ?exibly for decision makers’ attitude.
R 4,371.25
Linear Optimization Problems with Inexact Data
Linear programming has attracted the interest of mathematicians since World War II when the first computers were constructed. Early attempts to apply linear programming methods practical problems failed, in part because of the inexactness of the data used to create the models. This book presents a comprehensive treatment of linear optimization with inexact data, summarizing existing results and presenting new ones within a unifying framework.
R 2,015.00
Problem Solving and Uncertainty Modeling through Optimization and Soft Computing Applications
Optimization techniques have developed into a modern-day solution for real-world problems in various industries. As a way to improve performance and handle issues of uncertainty, optimization research becomes a topic of special interest across disciplines.Problem Solving and Uncertainty Modeling through Optimization and Soft Computing Applications presents the latest research trends and developments in the area of applied optimization methodologies and soft computing techniques for solving complex problems. Taking a multi-disciplinary approach, this critical publication is an essential reference source for engineers, managers, researchers, and post-graduate students.
R 8,729.23
Advanced Problem Solving Using Maple
Advanced Problem Solving Using Maple™: Applied Mathematics, Operations Research, Business Analytics, and Decision Analysis applies the mathematical modeling process by formulating, building, solving, analyzing, and criticizing mathematical models. Scenarios are developed within the scope of the problem-solving process.The text focuses on discrete dynamical systems, optimization techniques, single-variable unconstrained optimization and applied problems, and numerical search methods. Additional coverage includes multivariable unconstrained and constrained techniques. Linear algebra techniques to model and solve problems such as the Leontief model, and advanced regression techniques including nonlinear, logistics, and Poisson are covered. Game theory, the Nash equilibrium, and Nash arbitration are also included.Features: The text’s case studies and student projects involve students with real-world problem solving Focuses on numerical solution techniques in dynamical systems, optimization, and numerical analysis The numerical procedures discussed in the text are algorithmic and iterative Maple is utilized throughout the text as a tool for computation and analysis All algorithms are provided with step-by-step formats About the Authors:William P. Fox is an emeritus professor in the Department of Defense Analysis at the Naval Postgraduate School. Currently, he is an adjunct professor, Department of Mathematics, the College of William and Mary. He received his PhD at Clemson University and has many publications and scholarly activities including twenty books and over one hundred and fifty journal articles.William C. Bauldry, Prof. Emeritus and Adjunct Research Prof. of Mathematics at Appalachian State University, received his PhD in Approximation Theory from Ohio State. He has published many papers on pedagogy and technology, often using Maple, and has been the PI of several NSF-funded projects incorporating technology and modeling into math courses. He currently serves as Associate Director of COMAP’s Math Contest in Modeling (MCM).
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R 1,985.61
Modeling, Simulation and Optimization
This book includes selected peer-reviewed papers presented at the International Conference on Modeling, Simulation and Optimization, organized by National Institute of Technology, Silchar, Assam, India, during 3–5 August 2020. The book covers topics of modeling, simulation and optimization, including computational modeling and simulation, system modeling and simulation, device/VLSI modeling and simulation, control theory and applications, modeling and simulation of energy system and optimization. The book disseminates various models of diverse systems and includes solutions of emerging challenges of diverse scientific fields.
R 14,485.28
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 3,030.71
Modellbasierter Ansatz zur Ermittlung optimaler Hybrid-Antriebsstrangkonfigurationen unter Anwendung verschiedener Optimierungsalgorithmen
Ralf Georg Kleisch entwickelt einen Ansatz zum effizienten Auffinden optimaler Antriebsstrangkonfigurationen in großen Parameterräumen unter Anwendung verschiedener Betriebsstrategien. Durch die steigende Komplexität der Simulationsmodelle ist es, insbesondere auf Systemebene, erforderlich, den Auslegungs- und Dimensionierungsprozess mit Hilfe umfangreicher Simulationswerkzeuge effizient zu gestalten. Ein zentraler Aspekt der Studie liegt in der Integration verschiedener simulativer Ansätze und Granularitätsstufen im Auslegungsprozess, indem der entwickelte mehrstufige Simulations- und Optimierungsansatz einen effizienten und zweckmäßigen Einsatz eben dieser Granularitätsstufen ermöglicht.
R 4,212.57
Optimization in Computational Chemistry and Molecular Biology
Optimization in Computational Chemistry and Molecular Biology: Local and Global Approaches covers recent developments in optimization techniques for addressing several computational chemistry and biology problems. A tantalizing problem that cuts across the fields of computational chemistry, biology, medicine, engineering and applied mathematics is how proteins fold. Global and local optimization provide a systematic framework of conformational searches for the prediction of three-dimensional protein structures that represent the global minimum free energy, as well as low-energy biomolecular conformations. Each contribution in the book is essentially expository in nature, but of scholarly treatment. The topics covered include advances in local and global optimization approaches for molecular dynamics and modeling, distance geometry, protein folding, molecular structure refinement, protein and drug design, and molecular and peptide docking. Audience: The book is addressed not only to researchers in mathematical programming, but to all scientists in various disciplines who use optimization methods in solving problems in computational chemistry and biology.
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Handbook of Research on Modern Optimization Algorithms and Applications in Engineering and Economics
Modern optimization approaches have attracted many research scientists, decision makers and practicing researchers in recent years as powerful intelligent computational techniques for solving several complex real-world problems.The Handbook of Research on Modern Optimization Algorithms and Applications in Engineering and Economics highlights the latest research innovations and applications of algorithms designed for optimization applications within the fields of engineering, IT, and economics. Focusing on a variety of methods and systems as well as practical examples, this book is a significant resource for graduate-level students, decision makers, and researchers in both public and private sectors who are seeking research-based methods for modeling uncertain real-world problems.
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Topics in the Mathematical Modelling of Composite Materials
Andrej V. Cherkaev and Robert V. Kohn In the past twenty years we have witnessed a renaissance of theoretical work on the macroscopic behavior of microscopically heterogeneous mate rials. This activity brings together a number of related themes, including: ( 1) the use of weak convergence as a rigorous yet general language for the discussion of macroscopic behavior; (2) interest in new types of questions, particularly the "G-closure problem," motivated in large part by applications of optimal control theory to structural optimization; (3) the introduction of new methods for bounding effective moduli, including one based on "com pensated compactness"; and (4) the identification of deep links between the analysis of microstructures and the multidimensional calculus of variations. This work has implications for many physical problems involving optimal design, composite materials, and coherent phase transitions. As a result it has received attention and support from numerous scientific communities, including engineering, materials science, and physics as well as mathematics. There is by now an extensive literature in this area. But for various reasons certain fundamental papers were never properly published, circu lating instead as mimeographed notes or preprints. Other work appeared in poorly distributed conference proceedings volumes. Still other work was published in standard books or journals, but written in Russian or French. The net effect is a sort of "gap" in the literature, which has made the subject unnecessarily difficult for newcomers to penetrate.
R 6,007.01
Modeling and Optimization of Interdependent Energy Infrastructures
This book opens up new ways to develop mathematical models and optimization methods for interdependent energy infrastructures, ranging from the electricity network, natural gas network, district heating network, and electrified transportation network. The authors provide methods to help analyze, design, and operate the integrated energy system more efficiently and reliably, and constitute a foundational basis for decision support tools for the next-generation energy network. Chapters present new operation models of the coupled energy infrastructure and the application of new methodologies including convex optimization, robust optimization, and equilibrium constrained optimization. Four appendices provide students and researchers with helpful tutorials on advanced optimization methods: Basics of Linear and Conic Programs; Formulation Tricks in Integer Programming; Basics of Robust Optimization; Equilibrium Problems. This book provides theoretical foundation and technical applications for energy system integration, and the the interdisciplinary research presented will be useful to readers in many fields including electrical engineering, civil engineering, and industrial engineering.
R 6,553.04
Artificial Intelligence and Optimization Techniques for Smart Information System Generations
The text comprehensively focusses on the use of artificial intelligence and optimization techniques for creating smart information systems.Focuses on extracting information from blockchain repository using artificial intelligence and machine learning algorithmsPresents deep learning models to identify and locate objects within images and videos, making it possible for machines to perform tasks such as self-driving cars, surveillance, and roboticsDiscusses artificial intelligence and optimization techniques for geographic information system (GIS) generation such as spatial data processingCovers artificial intelligence algorithms such as dimensionality, distance metrics, clustering, error calculation, hill climbing, and linear regressionIllustrates topics such as image recognition, natural language processing, fraud detection, information system security, and intrusion detection system
R 2,711.00
Optimization in Artificial Intelligence and Data Sciences
This book is addressed to researchers in operations research, data science and artificial intelligence. It collects selected contributions from the first hybrid “Optimization and Decision Science - ODS2021” international conference on the theme Optimization and Artificial Intelligence and Data Sciences, which was held in Rome 14-17 September 2021 and organized by AIRO, the Italian Operations Research Society and the Department of Statistical Sciences of Sapienza University of Rome. The book offers new and original contributions on different methodological optimization topics, from Support Vector Machines to Game Theory Network Models, from Mathematical Programming to Heuristic Algorithms, and Optimization Methods for a number of emerging problems from Truck and Drone delivery to Risk Assessment, from Power Networks Design to Portfolio Optimization. The articles in the book can give a significant edge to the general themes of sustainability and pollution reduction, distributive logistics, healthcare management in pandemic scenarios and clinical trials, distributed computing, scheduling, and many others. For these reasons, the book is aimed not only at researchers in the Operations Research community but also for practitioners facing decision-making problems in these areas and to students and researchers from other disciplines, including Artificial Intelligence, Computer Sciences, Finance, Mathematics, and Engineering.
R 5,306.79
Econometric Modelling with Time Series
This book provides a general framework for specifying, estimating and testing time series econometric models. Special emphasis is given to estimation by maximum likelihood, but other methods are also discussed, including quasi-maximum likelihood estimation, generalised method of moments estimation, nonparametric estimation and estimation by simulation. An important advantage of adopting the principle of maximum likelihood as the unifying framework for the book is that many of the estimators and test statistics proposed in econometrics can be derived within a likelihood framework, thereby providing a coherent vehicle for understanding their properties and interrelationships. In contrast to many existing econometric textbooks, which deal mainly with the theoretical properties of estimators and test statistics through a theorem-proof presentation, this book squarely addresses implementation to provide direct conduits between the theory and applied work.
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Gradient Modelling
This series is dedicated to serving the growing community of scholars and practitioners concerned with the principles and applications of environmen tal management. Each volume will be a thorough treatment of a specific topic of importance for proper management practices. A fundamental objective ofthese books is to help the reader discern and implement man's stewardship of our environment and the world's renewable resources. For we must strive to understand the relationship between man and nature, act to bring harmony to it and nurture an environment that is both stable and productive. These objectives have often eluded us because the pursuit of other indi vidual and societal goals has diverted us from a course of living in balance with the environment. At times, therefore, the environmental manager may have to exert restrictive control, which is usually best applied to man, not nature. Attempts to alter or harness nature have often failed or backfired, as exemplified by the results of imprudent use of herbicides, fertilizers, water and other agents. Each book in this series will shed light on the fundamental and applied aspects of environmental management. It is hoped that each will help solve a practical and serious environmental problem.
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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.
R 4,007.64
Learning and Intelligent Optimization
This book constitutes the thoroughly refereed post-conference proceedings of the 9th International Conference on Learning and Optimization, LION 9, which was held in Lille, France, in January 2015.The 31 contributions presented were carefully reviewed and selected for inclusion in this book. The papers address all fields between machine learning, artificial intelligence, mathematical programming and algorithms for hard optimization problems. Special focus is given to algorithm selection and configuration, learning, fitness landscape, applications, dynamic optimization, multi-objective, max-clique problems, bayesian optimization and global optimization, data mining and - in a special session - also on dynamic optimization.
R 1,560.93
Empirical Modelling in Regional Science
Economic agents interact in structural relationships through time and space. This work starts from the empirical observation that all three dimensions, namely time, space, and structural functional forms, are important for an integrative framework of modern empirical analysis in regional science. The work thus aims at combining up-to-date econometric tools from the fields of spatial econometrics, panel time-series analysis and structural simultaneous equation modelling to analysis the different research questions at hand. Most of the topics dealt within this work start from a concrete empirical problem, while problem solving also aims at generating some new knowledge in a methodological way, e.g. by the complementary use of Monte Carlo simulation studies to compare the empirical performance of different estimators for specific data samples. Following a first introductory chapter, the work is structured in three parts addressing major issues in building up a stylized regional economic model such as interregional migration, factor and final demand estimation. All empirical applications use German regional data.
R 4,281.62
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.
R 4,250.88
Parallel Optimization
This book offers a unique pathway to methods of parallel optimization by introducing parallel computing ideas and techniques into both optimization theory, and into some numerical algorithms for large-scale optimization problems. The presentation is based on the recent understanding that rigorous mathematical analysis of algorithms, parallel computing techniques, and "hands-on" experimental work on real-world problems must go hand in hand in order to achieve thegreatest advantage from novel parallel computing architectures. The three parts of the book thus bring together relevant theory, careful study of algorithms, and modelling of significant real world problems. The problem domains include: image reconstruction, radiation therapy treatment planning,transportation problems, portfolilo management, and matrix estimation. This text can be used both as a reference for researchers and as a text for advanced graduate courses.
R 13,082.36
Modeling, Simulation and Optimization
This book includes selected peer-reviewed papers presented at the International Conference on Modeling, Simulation and Optimization, organized by National Institute of Technology, Silchar, Assam, India, during 3–5 August 2020. The book covers topics of modeling, simulation and optimization, including computational modeling and simulation, system modeling and simulation, device/VLSI modeling and simulation, control theory and applications, modeling and simulation of energy system and optimization. The book disseminates various models of diverse systems and includes solutions of emerging challenges of diverse scientific fields.
R 12,089.00
Optimization in Green Sustainability and Ecological Transition
This book collects selected contributions of the “Optimization and Decision Science - ODS2023” international conference on the theme of optimization in green sustainability and ecological transition. ODS2023 was held in Ischia, 4–7 September 2023, and was organized by AIRO, the Italian Operations Research Society. The book offers new and original contributions on operations research, optimization, decision science, and prescriptive analytics from both a methodological and applied perspectives with a special focus on SDG related topics.It provides a state-of-the art on problem models and solving methods to address a widely class of real-world problems, arising in different application areas such as logistics, transportation, manufacturing, health, ICT and mobile networks, and emergency/disaster management. In addition, the scientific works collected in this book aim at providing significant contributions in the themes of sustainability, traffic and pollution reductions, and energy management.This book is aimed primarily at researchers and Ph.D. students in the Operations Research community. However, due to its interdisciplinary contents, this book is of high interest also for students and researchers from other disciplines, including artificial intelligence, computer sciences, finance, mathematics, and engineering as well as for practitioners facing complex decision-making problems in logistics, manufacturing production, and services.
R 10,257.00
Modeling, Simulation and Optimization of Complex Processes
High Performance Scienti?c Computing is an interdisciplinary area that combines many ?elds such as mathematics, computer science and scienti?c and engineering applications. It is a key high-technology for competitiveness in industrialized countries as well as for speeding up development in emerging countries. High performance scienti?c computing develops methods for c- puteraidedsimulationandoptimizationofsystemsandprocesses.Inpractical applications in industry and commerce, science and engineering, it helps to save resources, to avoid pollution, to reduce risks and costs, to improve pr- uctquality,toshortendevelopmenttimesorsimplytooperatesystemsbetter. Di?erent aspects of scienti?c computing have been the topics of the Third International Conference on High Performance Scienti?c Computing held at the Hanoi Institute of Mathematics, Vietnamese Academy of Science and Technology (VAST), March 6-10, 2006. The conference has been organized by the Hanoi Institute of Mathematics, Ho Chi Minh City University of Te- nology, Interdisciplinary Center for Scienti?c Computing (IWR), Heidelberg, and its International PhD Program "Complex Processes: Modeling, Simu- tion and Optimization".The conference had about 200 participants from countries all over the world.Thescienti?cprogramconsistedofmorethan130talks,10ofthemwere invited plenary talks given by John Ball (Oxford), Vincenzo Capasso (Milan), PaoloCarloni(Trieste),SebastianEngell(Dortmund),DonaldGoldfarb(New York), Wolfgang Hackbusch (Leipzig), Satoru Iwata (Tokyo), Hans Petter Langtangen (Oslo), Tao Tang (Hong Kong) and Philippe Toint (Namur).
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Practical Bilevel Optimization
The use of optimization techniques has become integral to the design and analysis of most industrial and socio-economic systems. Great strides have been made recently in the solution of large-scale problems arising in such areas as production planning, airline scheduling, government regulation, and engineering design, to name a few. Analysts have found, however, that standard mathematical programming models are often inadequate in these situations because more than a single objective function and a single decision maker are involved. Multiple objective programming deals with the extension of optimization techniques to account for several objective functions, while game theory deals with the inter-personal dynamics surrounding conflict. Bilevel programming, the focus of this book, is in a narrow sense the combination of the two. It addresses the problern in which two decision makers, each with their individual objectives, act and react in a noncooperative, sequential manner. The actions of one affect the choices and payoffs available to the other but neither player can completely dominate the other in the traditional sense.
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Linear and Mixed Integer Programming for Portfolio Optimization
This book presents solutions to the general problem of single period portfolio optimization. It introduces different linear models, arising from different performance measures, and the mixed integer linear models resulting from the introduction of real features. Other linear models, such as models for portfolio rebalancing and index tracking, are also covered. The book discusses computational issues and provides a theoretical framework, including the concepts of risk-averse preferences, stochastic dominance and coherent risk measures. The material is presented in a style that requires no background in finance or in portfolio optimization; some experience in linear and mixed integer models, however, is required. The book is thoroughly didactic, supplementing the concepts with comments and illustrative examples.
R 2,717.84
Molecular Data Analysis Using R
This book addresses the difficulties experienced by wet lab researchers with the statistical analysis of molecular biology related data. The authors explain how to use R and Bioconductor for the analysis of experimental data in the field of molecular biology. The content is based upon two university courses for bioinformatics and experimental biology students (Biological Data Analysis with R and High-throughput Data Analysis with R). The material is divided into chapters based upon the experimental methods used in the laboratories. Key features include:• Broad appeal--the authors target their material to researchers in several levels, ensuring that the basics are always covered.• First book to explain how to use R and Bioconductor for the analysis of several types of experimental data in the field of molecular biology.• Focuses on R and Bioconductor, which are widely used for data analysis. One great benefit of R and Bioconductor is that there is a vast user community and very active discussion in place, in addition to the practice of sharing codes. Further, R is the platform for implementing new analysis approaches, therefore novel methods are available early for R users.
R 3,516.00
Advances in Multidisciplinary Analysis and Optimization
This volume contains select papers presented during the 2nd National Conference on Multidisciplinary Analysis and Optimization. It discusses new developments at the core of optimization methods and its application in multiple applications. The papers showcase fundamental problems and applications which include domains such as aerospace, automotive and industrial sectors. The variety of topics and diversity of insights presented in the general field of optimization and its use in design for different applications will be of interest to researchers in academia or industry.
R 5,380.42
Modern Music-Inspired Optimization Algorithms for Electric Power Systems
In today’s world, with an increase in the breadth and scope of real-world engineering optimization problems as well as with the advent of big data, improving the performance and efficiency of algorithms for solving such problems has become an indispensable need for specialists and researchers. In contrast to conventional books in the field that employ traditional single-stage computational, single-dimensional, and single-homogeneous optimization algorithms, this book addresses multiple newfound architectures for meta-heuristic music-inspired optimization algorithms. These proposed algorithms, with multi-stage computational, multi-dimensional, and multi-inhomogeneous structures, bring about a new direction in the architecture of meta-heuristic algorithms for solving complicated, real-world, large-scale, non-convex, non-smooth engineering optimization problems having a non-linear, mixed-integer nature with big data. The architectures of these new algorithms may also be appropriate for finding an optimal solution or a Pareto-optimal solution set with higher accuracy and speed in comparison to other optimization algorithms, when feasible regions of the solution space and/or dimensions of the optimization problem increase. This book, unlike conventional books on power systems problems that only consider simple and impractical models, deals with complicated, techno-economic, real-world, large-scale models of power systems operation and planning. Innovative applicable ideas in these models make this book a precious resource for specialists and researchers with a background in power systems operation and planning.Provides an understanding of the optimization problems and algorithms, particularly meta-heuristic optimization algorithms, found in fields such as engineering, economics, management, and operations research;Enhances existing architectures and develops innovative architectures for meta-heuristic music-inspired optimization algorithms in order to deal with complicated, real-world, large-scale, non-convex, non-smooth engineering optimization problems having a non-linear, mixed-integer nature with big data;Addresses innovative multi-level, techno-economic, real-world, large-scale, computational-logical frameworks for power systems operation and planning, and illustrates practical training on implementation of the frameworks using the meta-heuristic music-inspired optimization algorithms.
R 8,059.00
Modeling, Simulation and Optimization of Complex Processes HPSC 2015
This proceedings volume highlights a selection of papers presented at the Sixth International Conference on High Performance Scientific Computing, which took place in Hanoi, Vietnam on March 16-20, 2015. The conference was jointly organized by the Heidelberg Institute of Theoretical Studies (HITS), the Institute of Mathematics of the Vietnam Academy of Science and Technology (VAST), the Interdisciplinary Center for Scientific Computing (IWR) at Heidelberg University, and the Vietnam Institute for Advanced Study in Mathematics, Ministry of Education The contributions cover a broad, interdisciplinary spectrum of scientific computing and showcase recent advances in theory, methods, and practical applications. Subjects covered numerical simulation, methods for optimization and control, parallel computing, and software development, as well as the applications of scientific computing in physics, mechanics, biomechanics and robotics, material science, hydrology, biotechnology, medicine, transport, scheduling, and industry.
R 3,681.93
Operations Research Using Excel
The field of operations research provides a scientific approach to managerial decision making. In a contemporary, hypercompetitive ever-changing business world, a manager needs quantitative and factual ways of solving problems related to optimal allocation of resources, profit/loss, maximization/minimization etc. In this endeavor, the subject of doing research on how to manage and make operations efficient is termed as Operations Research. The reference text provides conceptual and analytical knowledge for various operations research techniques. Readers, especially students of this subject, are skeptic in dealing with the subject because of its emphasis on mathematics. However, this book has tried to remove such doubts by focusing on the application part of OR techniques with minimal usage of mathematics. The attempt was to make students comfortable with some complicated topics of the subject. It covers important concepts including sensitivity analysis, duality theory, transportation solution method, Hungarian algorithm, program evaluation and review technique and periodic review system. Aimed at senior undergraduate and graduate students in the fields of mechanical engineering, civil engineering, industrial engineering and production engineering, this book:• Discusses extensive use of Microsoft Excel spreadsheets and formulas in solving operations research problems• Provides case studies and unsolved exercises at the end of each chapter• Covers industrial applications of various operations research techniques in a comprehensive manner• Discusses creating spreadsheets and using different Excel formulas in an easy-to-understand manner• Covers problem-solving procedures for techniques including linear programming, transportation model and game theory
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Nonlinear Financial Econometrics: Forecasting Models, Computational and Bayesian Models
This book investigates several competing forecasting models for interest rates, financial returns, and realized volatility, addresses the usefulness of nonlinear models for hedging purposes, and proposes new computational techniques to estimate financial processes.
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Business Optimization Using Mathematical Programming
This book presents a structured approach to formulate, model, and solve mathematical optimization problems for a wide range of real world situations. Among the problems covered are production, distribution and supply chain planning, scheduling, vehicle routing, as well as cutting stock, packing, and nesting. The optimization techniques used to solve the problems are primarily linear, mixed-integer linear, nonlinear, and mixed integer nonlinear programming. The book also covers important considerations for solving real-world optimization problems, such as dealing with valid inequalities and symmetry during the modeling phase, but also data interfacing and visualization of results in a more and more digitized world. The broad range of ideas and approaches presented helps the reader to learn how to model a variety of problems from process industry, paper and metals industry, the energy sector, and logistics using mathematical optimization techniques.
R 4,030.00
Portfolio Optimization
Eschewing a more theoretical approach, Portfolio Optimization shows how the mathematical tools of linear algebra and optimization can quickly and clearly formulate important ideas on the subject. This practical book extends the concepts of the Markowitz "budget constraint only" model to a linearly constrained model.Only requiring elementary linear algebra, the text begins with the necessary and sufficient conditions for optimal quadratic minimization that is subject to linear equality constraints. It then develops the key properties of the efficient frontier, extends the results to problems with a risk-free asset, and presents Sharpe ratios and implied risk-free rates. After focusing on quadratic programming, the author discusses a constrained portfolio optimization problem and uses an algorithm to determine the entire (constrained) efficient frontier, its corner portfolios, the piecewise linear expected returns, and the piecewise quadratic variances. The final chapter illustrates infinitely many implied risk returns for certain market portfolios.Drawing on the author’s experiences in the academic world and as a consultant to many financial institutions, this text provides a hands-on foundation in portfolio optimization. Although the author clearly describes how to implement each technique by hand, he includes several MATLAB® programs designed to implement the methods and offers these programs on the accompanying downloadable resources.
R 6,118.00
Systems Modelling and Optimization Proceedings of the 18th IFIP TC7 Conference
Top researchers in optimization and control from around the world gathered in Detroit for the 18th annual IFIP TC7 Conference on Systems Modelling and Optimization held in July 1997. The papers offered in this volume were selected from among the 250 plenary, invited, and contributed works presented at the conference. The editors chose these papers to represent the myriad and diverse range of topics within the field -in theory and applications-and to disseminate important new results.The editors have organized the book into seven sections: Distributed Parameter Systems Modelling Optimal Control and Nonsmoooth Analysis Automotive Optimization and Operations Research Applications Reliability Each section contains important advances in theoretical development of optimization and control, new results, and discussions of applications. Treatment of numerous and wide- ranging applications-from turbulent flows, European option pricing, and storage location, to wear processes, passive fire protection, and robotics-make this resource important for academic and industrial researchers working in a variety of areas in systems engineering and applied mathematics.
R 6,960.00
Modeling and Optimization of the Lifetime of Technologies
Modern economic growth is characterized by structural changes based on the introduction of new technologies into economics. The replacement and renova tion of technologies in industrial environments undergoing technical change is clearly one of the key aspects of economic development. The mathematical modeling of evolutionary economics under technical change (TC) has been rigorously considered by many authors during last decades. There is a wide variety of economic approaches and models describing different aspects of technical change. Among these are the models of embodied technical progress [19], [35], [70], [129], endogenous growth models [94], [102], the models of technological innovations [31], [32], [41], and others. The perspective self organization evolutionary approach is developed in [20], [38], [122], [123], [124], [126], which unites the aspects of diffusion of new technologies, technological and behavioral diversity of firms, learning mechanisms, age-dependent effects, and other important features of real-life economics. On the whole, an interest in evolutionary economics has brought considerable progress in the description and conceptualization of the sources, characteristics, direction and effects of technical change [125]. However, the modeling and control of technology lifetime under technical change has received rather little attention in mathematical economics in con trary to other aspects of technical progress. The lifetime of technologies has rarely been formally treated as a part of more general mathematical theory of economic dynamics. A problem which is still to be resolved consists in establishing the rational strategies of technologies' replacement under various assumptions on the behavior of technical change.
R 3,035.54
Design Optimization using MATLAB and SOLIDWORKS
A unique text integrating numerics, mathematics and applications to provide a hands-on approach to using optimization techniques, this mathematically accessible textbook emphasises conceptual understanding and importance of theorems rather than elaborate proofs. It allows students to develop fundamental optimization methods before delving into MATLAB®'s optimization toolbox, and to link MATLAB's results with the results from their own code. Following a practical approach, the text demonstrates several applications, from error-free analytic examples to truss (size) optimization, and 2D and 3D shape optimization, where numerical errors are inevitable. The principle of minimum potential energy is discussed to highlight the deep relationship between engineering and optimization. MATLAB code in every chapter illustrates key concepts and the text demonstrates the coupling between MATLAB and SOLIDWORKS® for design optimization. A wide variety of optimization problems are covered including constrained non-linear, linear-programming, least-squares, multi-objective, and global optimization problems.
R 4,873.00
Introduction to Structural Optimization
This book has grown out of lectures and courses given at Linköping University, Sweden, over a period of 15 years. It gives an introductory treatment of problems and methods of structural optimization. The three basic classes of geometrical - timization problems of mechanical structures, i. e. , size, shape and topology op- mization, are treated. The focus is on concrete numerical solution methods for d- crete and (?nite element) discretized linear elastic structures. The style is explicit and practical: mathematical proofs are provided when arguments can be kept e- mentary but are otherwise only cited, while implementation details are frequently provided. Moreover, since the text has an emphasis on geometrical design problems, where the design is represented by continuously varying—frequently very many— variables, so-called ?rst order methods are central to the treatment. These methods are based on sensitivity analysis, i. e. , on establishing ?rst order derivatives for - jectives and constraints. The classical ?rst order methods that we emphasize are CONLIN and MMA, which are based on explicit, convex and separable appro- mations. It should be remarked that the classical and frequently used so-called op- mality criteria method is also of this kind. It may also be noted in this context that zero order methods such as response surface methods, surrogate models, neural n- works, genetic algorithms, etc. , essentially apply to different types of problems than the ones treated here and should be presented elsewhere.
R 1,948.13
Heuristische Optimierung von Simulationsmodellen mit dem Razor Search-Algorithmus
Ais ein wesentlicher Unterschied zwischen der Unternehmensforschung (Operations Research) und der Systemforschung (Systems Research) wird herausgestellt, daB hier heuristische und dort analytische Verfahren zum Einsatz kommen. Wenn dies so ist, dann haben diese beiden groBen Entwicklungen, denen so viele Wissenschaften so viel zu verdanken haben, irgendwo ihre Grenzen; sei es, daB bestimmte Probleme entweder nur heuristisch oder nur analytisch anzugehen sind. Dazu mUssen manche von en sehr weitgehend, oft zu weitgehend vereinfacht werden, damit sie einem analytischen Ansatz zug1inglich sind; dazu mUssen andere Probleme als Fragen so formuliert werden, daB dar auf keine eindeutige Antwort zu geben ist, sondern nur Aussagen in Wenn: Dann -Relationen. Beides ist oft unbefriedigend. In dieser Situation bemiiht man sich urn das Weiterentwickeln der verfUgbaren Methoden in der Weise, daB Synthesen zwischen demheuristischen und dem analytischen Vor- gehen gesucht werden. Eine solche Synthese hat Hermann Krallmann mit der Integration nichtlinearer Optimierungsalgorithmen in ein Modell yom System Dynamics -Typ offenkundig gefun en. Damit ist ein Weg gewiesen, auf dem fortzuschreiten lohnend erscheint, nachdem die erste Station dieses Weges jetzt klar dargestellt und somit fur jeder- mann erreichbar ist. Die geschaffene Methode ist n1imlich so einleuchtend, daB sie ohne MUhe zu verstehen und anzuwenden ist, wozu deren ausfUhrliche Darlegung mit einem Beispiel und die beigegebene Computersoftware erheblich beitragen. Auf diese Weise wird jeder in der Praxis tatige System-und Unternehmensforscher ebenso direkt angesprochen wie jeder Wissenschaftler in den vielen Disziplinen, die heute ohne computergestutztes Denken und Rechnen nicht mehr leistungsfahig sein konnen.
R 1,140.00
Economic and Financial Modeling with Mathematica®
Mathematica is a computer program (software) for doing symbolic, numeric and graphical analysis of mathematical problems. In the hands of economists, financial analysts and other professionals in econometrics and the quantitative sector of economic and financial modeling, it can be an invaluable tool for modeling and simulation on a large number of issues and problems, besides easily grinding out numbers, doing statistical estimations and rendering graphical plots and visuals. Mathematica enables these individuals to do all of this in a unified environment. This book's main use is that of an applications handbook. Modeling in Economics and Finance with Mathematica is a compilation of contributed papers prepared by experienced, "hands on" users of the Mathematica program. They come from
R 1,752.63
Throughput Optimization in Robotic Cells
Throughput Optimization In Robotic Cells provides practitioners, researchers, and students with up-to-date algorithmic results on sequencing of robot moves and scheduling of parts in robotic cells. It brings together the structural results developed over the last 25 years for the various realistic models of robotic cells. This book is ideally suited for use in a graduate course or a research seminar on robotic cells.
R 4,396.00
Optimization in Economics and Finance
Some recent developments in the mathematics of optimization, including the concepts of invexity and quasimax, have not yet been applied to models of economic growth, and to finance and investment. Their applications to these areas are shown in this book.
R 4,030.00
Stochastic Optimization for Large-scale Machine Learning
Advancements in the technology and availability of data sources have led to the `Big Data' era. Working with large data offers the potential to uncover more fine-grained patterns and take timely and accurate decisions, but it also creates a lot of challenges such as slow training and scalability of machine learning models. One of the major challenges in machine learning is to develop efficient and scalable learning algorithms, i.e., optimization techniques to solve large scale learning problems.Stochastic Optimization for Large-scale Machine Learning identifies different areas of improvement and recent research directions to tackle the challenge. Developed optimisation techniques are also explored to improve machine learning algorithms based on data access and on first and second order optimisation methods.Key Features:Bridges machine learning and Optimisation.Bridges theory and practice in machine learning.Identifies key research areas and recent research directions to solve large-scale machine learning problems.Develops optimisation techniques to improve machine learning algorithms for big data problems.The book will be a valuable reference to practitioners and researchers as well as students in the field of machine learning.
R 9,956.45
