As the demand for energy continues to grow, optimization has risen to the forefront of power engineering research and development. Continuing in the bestselling tradition of the first edition, Electric Power System Applications of Optimization, Second Edition presents the theoretical background of optimization from a practical power system point of view, exploring advanced techniques, new directions, and continuous application problems.
The book provides both the analytical formulation of optimization and various algorithmic issues that arise in the application of various methods in power system planning and operation. The second edition adds new functions involving market programs, pricing, reliability, and advances in intelligent systems with implemented algorithms and illustrative examples. It describes recent developments in the field of Adaptive Critics Design and practical applications of approximate dynamic programming. To round out the coverage, the final chapter combines fundamental theories and theorems from functional optimization, optimal control, and dynamic programming to explain new Adaptive Dynamic Programming concepts and variants.
With its one-of-a-kind integration of cornerstone optimization principles with application examples, this second edition propels power engineers to new discoveries in providing optimal supplies of energy.
Presenting the science of statistical process control (SPC) and the related concepts of total quality management (TQM) and design of experiments (DOE), this remarkable reference demonstrates ways to track industrial processes and performance -- integrating related areas such as engineering process control, statistical reasoning in TQM, robust parameter design, control charts, multivariate process monitoring, capability indices, experimental design, empirical model building, and process optimization. Written by more than 25 renowned researchers with broad experience with on-the-job problem solving, Statistical Process Monitoring and Optimization showcases concepts such as "people-based management" and continuous improvement...examines leadership styles in European, American, and Asian companies...describes means of quantifying factors such as employee loyalty and customer satisfaction and their relation to profitability...explores multivariate diagnosis theory in application to multioperational and multi-index systems...assesses uses of Markov chains in relation to ARL and associated sampling distributions...explains statistical models for dynamic systems, change-point analysis, generalized linear models, and key algorithms...elucidates replication strategies and process capability...reviews the interplay of intraorganizational domains such as finance, marketing, resource allocation, software engineering, and strategic planning...and more. Containing over 1000 references, drawings, tables, and equations, Statistical Process Monitoring and Optimization is a must-read resource for applied statisticians; industrial, quality control, and management science engineers; and upper-level undergraduate and graduate students in these disciplines. Book jacket.
This volume contains the proceedings of the workshop on Optimization Theory and Related Topics, held in memory of Dan Butnariu, from January 11-14, 2010, in Haifa, Israel. An active researcher in various fields of applied mathematics, Butnariu published over 80 papers. His extensive bibliography is included in this volume. The articles in this volume cover many different areas of Optimization Theory and its applications: maximal monotone operators, sensitivity estimates via Lyapunov functions, inverse Newton transforms, infinite-horizon Pontryagin principles, singular optimal control problems with state delays, descent methods for mixed variational inequalities, games on MV-algebras, ergodic convergence in subgradient optimization, applications to economics and technology planning, the exact penalty property in constrained optimization, nonsmooth inverse problems, Bregman distances, retraction methods in Banach spaces, and iterative methods for solving equilibrium problems. This volume will be of interest to both graduate students and research mathematicians.
Criminological research lies at the heart of criminological theory, influences social policy development, as well as informs criminal justice practice. The ability to collect, analyse and present empirical data is a core skill every student of criminology must learn. Written as an engaging step-by-step guide and illustrated by detailed case studies, this book guides the reader in how to analyse criminological data. Key features of the book include: o Guidance on how to identify a research topic and question, design a research study, account for the role of the researcher within the research process, as well as write up and present research findings. o A thorough account of the development of qualitative and quantitative research methodologies within the emergence of criminology as an academic discipline; including experimental research design, survey research, qualitative approaches and mixed methods. o Detailed coverage of different forms of qualitative and quantitative data analysis used by criminologists and other social scientists; including grounded theory, narrative analysis, discourse analysis, as well as descriptive and inferential statistics. o Relevant and up-to-date case studies, drawn from internationally published criminological research sources, to illustrate how to conduct different types of data analysis. o Clear and accessible chapter content supported by helpful introductions, concise summaries, self-study questions and suggestions for further reading.
The classic introduction to engineering optimization theory and practice--now expanded and updated<br> <br> <br> 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:<br> * Practical issues, such as model formulation, implementation, starting point generation, and more<br> * Current, state-of-the-art optimization software<br> * Three engineering case studies plus numerous examples from chemical, industrial, and mechanical engineering<br> * Both classical methods and new techniques, such as successive quadratic programming, interior point methods, and goal programming<br> <br> 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.
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