Tag: OPTIMIZATION

Free Download Stability and Optimization of Flexible Space Structures By Univ. Prof. S. J. Britvec (auth.)
1995 | 280 Pages | ISBN: 303489886X | PDF | 7 MB
The aim of this book is to present up-to-date methodologies in the analysis and optimization of the elastic stability of lightweight statically determinate, and in- determinate, space structures made of flexible members which are highly stiff when loaded centrally at the nodes. These are flat and curved space pin- connected open or enveloped lattices and reticulated shells which, due to their high loadbearing capacity to weight ratios, are gaining in importance in aerospace and other fields. They are utilized, for example, in space stations, as support structures for large radio-telescopes and for other equipment on earth and in outer space, as roof structures for the coverage and enclosure of large areas on earth and as underwater shell-type structures enveloped by a cover-shell capable of withstanding high hydrostatic pressures. * Space structures of this type are generally subjected to considerable internal axial loads in the flexible members and they fail through the loss of global statical stability, usually precipitated by the intrinsic small imperfections at finite near-critical elastic deformations – and not primarily by the the break-down of the material of which they are made, as is the case in conventional systems. Thus, the criterion in the design of such structures calls for eliminating or isolating the onset of the elastic dynamic collapse thereby increasing their safe stability limit. * Standard finite element methods, as they are employed by most users today, are totally inadequate for such analyses since they do not account for the choice of the branching paths in the loading process of the structure nor for the existence of the relevant collapse modes. * These aspects are novel and they are presented here for the first time in comprehensive book form.

Free Download Pyomo – Optimization Modeling in Python By William E. Hart, Carl Laird, Jean-Paul Watson, David L. Woodruff (auth.)
2012 | 238 Pages | ISBN: 1461432251 | PDF | 2 MB
This book provides a complete and comprehensive reference/guide to Pyomo (Python Optimization Modeling Objects) for both beginning and advanced modelers, including students at the undergraduate and graduate levels, academic researchers, and practitioners. The text illustrates the breadth of the modeling and analysis capabilities that are supported by the software and support of complex real-world applications. Pyomo is an open source software package for formulating and solving large-scale optimization and operations research problems. The text begins with a tutorial on simple linear and integer programming models. A detailed reference of Pyomo’s modeling components is illustrated with extensive examples, including a discussion of how to load data from data sources like spreadsheets and databases. Chapters describing advanced modeling capabilities for nonlinear and stochastic optimization are also included. The Pyomo software provides familiar modeling features within Python, a powerful dynamic programming language that has a very clear, readable syntax and intuitive object orientation. Pyomo includes Python classes for defining sparse sets, parameters, and variables, which can be used to formulate algebraic expressions that define objectives and constraints. Moreover, Pyomo can be used from a command-line interface and within Python’s interactive command environment, which makes it easy to create Pyomo models, apply a variety of optimizers, and examine solutions. The software supports a different modeling approach than commercial AML (Algebraic Modeling Languages) tools, and is designed for flexibility, extensibility, portability, and maintainability but also maintains the central ideas in modern AMLs.

Free Download Optimization of Spiking Neural Networks for Radar Applications by Muhammad Arsalan
English | September 2, 2024 | ISBN: 3658453176 | 260 pages | MOBI | 18 Mb
This book offers a comprehensive exploration of the transformative role that edge devices play in advancing Internet of Things (IoT) applications. By providing real-time processing, reduced latency, increased efficiency, improved security, and scalability, edge devices are at the forefront of enabling IoT growth and success. As the adoption of AI on the edge continues to surge, the demand for real-time data processing is escalating, driving innovation in AI and fostering the development of cutting-edge applications and use cases. Delving into the intricacies of traditional deep neural network (deepNet) approaches, the book addresses concerns about their energy efficiency during inference, particularly for edge devices. The energy consumption of deepNets, largely attributed to Multiply-accumulate (MAC) operations between layers, is scrutinized. Researchers are actively working on reducing energy consumption through strategies such as tiny networks, pruning approaches, and weight quantization. Additionally, the book sheds light on the challenges posed by the physical size of AI accelerators for edge devices. The central focus of the book is an in-depth examination of SNNs’ capabilities in radar data processing, featuring the development of optimized algorithms.

Free Download Handbook on Semidefinite, Conic and Polynomial Optimization By Miguel F. Anjos, Jean B. Lasserre (auth.), Miguel F. Anjos, Jean B. Lasserre (eds.)
2012 | 957 Pages | ISBN: 1461407680 | PDF | 9 MB
Semidefinite and conic optimization is a major and thriving research area within the optimization community. Although semidefinite optimization has been studied (under different names) since at least the 1940s, its importance grew immensely during the 1990s after polynomial-time interior-point methods for linear optimization were extended to solve semidefinite optimization problems. Since the beginning of the 21st century, not only has research into semidefinite and conic optimization continued unabated, but also a fruitful interaction has developed with algebraic geometry through the close connections between semidefinite matrices and polynomial optimization. This has brought about important new results and led to an even higher level of research activity. This Handbook on Semidefinite, Conic and Polynomial Optimization provides the reader with a snapshot of the state-of-the-art in the growing and mutually enriching areas of semidefinite optimization, conic optimization, and polynomial optimization. It contains a compendium of the recent research activity that has taken place in these thrilling areas, and will appeal to doctoralstudents, young graduates, and experienced researchers alike. The Handbook’s thirty-one chapters are organized into four parts:Theory, covering significant theoretical developments as well as the interactions between conic optimization and polynomial optimization;Algorithms, documenting the directions of current algorithmic development;Software, providing an overview of the state-of-the-art;Applications, dealing with the application areas where semidefinite and conic optimization has made a significant impact in recent years.

Free Download Optimization Algorithms, Video Edition by Alaa Khamis
Released: 10/2024
Duration: 15h 54m | .MP4 1920×1080, 30 fps(r) | AAC, 48000 Hz, 2ch | 3 GB
Genre: eLearning | Language: English
In Video Editions the narrator reads the book while the content, figures, code listings, diagrams, and text appear on the screen. Like an audiobook that you can also watch as a video.

Free Download Stochastic Recursive Algorithms for Optimization: Simultaneous Perturbation Methods By S. Bhatnagar, H.L. Prasad, L.A. Prashanth (auth.)
2013 | 302 Pages | ISBN: 1447142845 | PDF | 3 MB
Stochastic Recursive Algorithms for Optimization presents algorithms for constrained and unconstrained optimization and for reinforcement learning. Efficient perturbation approaches form a thread unifying all the algorithms considered. Simultaneous perturbation stochastic approximation and smooth fractional estimators for gradient- and Hessian-based methods are presented. These algorithms: * are easily implemented; * do not require an explicit system model; and * work with real or simulated data. Chapters on their application in service systems, vehicular traffic control and communications networks illustrate this point. The book is self-contained with necessary mathematical results placed in an appendix. The text provides easy-to-use, off-the-shelf algorithms that are given detailed mathematical treatment so the material presented will be of significant interest to practitioners, academic researchers and graduate students alike. The breadth of applications makes the book appropriate for reader from similarly diverse backgrounds: workers in relevant areas of computer science, control engineering, management science, applied mathematics, industrial engineering and operations research will find the content of value.

Free Download Metaheuristics Algorithm and Optimization of Engineering and Complex Systems by Thanigaivelan R, Suchithra M, Kaliappan S
English | July 23, 2024 | ISBN: 836935002X | 424 pages | PDF | 6.58 Mb
In the field of engineering, optimization and decision-making have become pivotal concerns. The ever-increasing demand for data processing has given rise to issues such as extended processing times and escalated memory utilization, posing formidable obstacles across various engineering domains. Problems persist, requiring not only solutions but advancements beyond existing best practices. Creating and implementing novel heuristic algorithms is a time-intensive process, yet the imperative to do so remains strong, driven by the potential to significantly lower computational costs even with marginal improvements. This book, titled Metaheuristics Algorithm and Optimization of Engineering and Complex Systems, is a beacon of innovation in this context. It examines the critical need for inventive algorithmic solutions, exploring hyperheuristic approaches that offer solutions such as automating search spaces through integrated heuristics. Designed to cater to a broad audience, this book is a valuable resource for both novice and experienced dynamic optimization practitioners. By addressing the spectrum of theory and practice, as well as discrete versus continuous dynamic optimization, it becomes an indispensable reference in a captivating and emerging field. With a deliberate focus on inclusivity, the book is poised to benefit anyone with an interest in staying abreast of the latest developments in dynamic optimization.

Free Download Cutting Optimization Pro 5.18.0.70 Multilingual Fast Links | 1.8 Mb
Cutting Optimization Pro is a cutting software used for obtaining optimal cutting layouts for one (1D) and two (2D) dimensional pieces. The software also lets you to define and handle complex products, such as table, desk, cupboard, locker, book shelf.

Free Download Cutting Optimization Pro 5.18.0.67 Multilingual Fast Links | 1.8 Mb
Cutting Optimization Pro is a cutting software used for obtaining optimal cutting layouts for one (1D) and two (2D) dimensional pieces. The software also lets you to define and handle complex products, such as table, desk, cupboard, locker, book shelf.

Free Download Cutting Optimization Pro 5.18.0.66 Multilingual Fast Links | 1.8 Mb
Cutting Optimization Pro is a cutting software used for obtaining optimal cutting layouts for one (1D) and two (2D) dimensional pieces. The software also lets you to define and handle complex products, such as table, desk, cupboard, locker, book shelf.