Encyclopedia of Optimization
Encyclopedia of Optimization

Author: Christodoulos A. Floudas

Publisher: Springer Science & Business Media

Published: 2008-09-04

Total Pages: 4646

ISBN-13: 0387747583

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The goal of the Encyclopedia of Optimization is to introduce the reader to a complete set of topics that show the spectrum of research, the richness of ideas, and the breadth of applications that has come from this field. The second edition builds on the success of the former edition with more than 150 completely new entries, designed to ensure that the reference addresses recent areas where optimization theories and techniques have advanced. Particularly heavy attention resulted in health science and transportation, with entries such as "Algorithms for Genomics", "Optimization and Radiotherapy Treatment Design", and "Crew Scheduling".

Large Scale Optimization in Supply Chains and Smart Manufacturing
Large Scale Optimization in Supply Chains and Smart Manufacturing

Author: Jesús M. Velásquez-Bermúdez

Publisher: Springer Nature

Published: 2019-09-06

Total Pages: 297

ISBN-13: 303022788X

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In this book, theory of large scale optimization is introduced with case studies of real-world problems and applications of structured mathematical modeling. The large scale optimization methods are represented by various theories such as Benders’ decomposition, logic-based Benders’ decomposition, Lagrangian relaxation, Dantzig –Wolfe decomposition, multi-tree decomposition, Van Roy’ cross decomposition and parallel decomposition for mathematical programs such as mixed integer nonlinear programming and stochastic programming. Case studies of large scale optimization in supply chain management, smart manufacturing, and Industry 4.0 are investigated with efficient implementation for real-time solutions. The features of case studies cover a wide range of fields including the Internet of things, advanced transportation systems, energy management, supply chain networks, service systems, operations management, risk management, and financial and sales management. Instructors, graduate students, researchers, and practitioners, would benefit from this book finding the applicability of large scale optimization in asynchronous parallel optimization, real-time distributed network, and optimizing the knowledge-based expert system for convex and non-convex problems.

Handbook of Military Industrial Engineering
Handbook of Military Industrial Engineering

Author: Adedeji B. Badiru

Publisher: CRC Press

Published: 2009-02-25

Total Pages: 830

ISBN-13: 1420066293

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In light of increasing economic and international threats, military operations must be examined with a critical eye in terms of process design, management, improvement, and control. Although the Pentagon and militaries around the world have utilized industrial engineering (IE) concepts to achieve this goal for decades, there has been no single reso

Handbook of Combinatorial Optimization
Handbook of Combinatorial Optimization

Author: Ding-Zhu Du

Publisher: Springer Science & Business Media

Published: 2006-08-18

Total Pages: 395

ISBN-13: 0387238301

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This is a supplementary volume to the major three-volume Handbook of Combinatorial Optimization set. It can also be regarded as a stand-alone volume presenting chapters dealing with various aspects of the subject in a self-contained way.

Transport Simulation
Transport Simulation

Author: Edward Chung

Publisher: CRC Press

Published: 2019-05-07

Total Pages: 200

ISBN-13: 042952613X

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In recent years, the transport simulation of large road networks has become far more rapid and detailed, and many exciting developments in this field have emerged. Within this volume, the authors describe the simulation of automobile, pedestrian, and rail traffic coupled to new applications, such as the embedding of traffic simulation into driving simulators, to give a more realistic environment of driver behavior surrounding the subject vehicle. New approaches to traffic simulation are described, including the hybrid mesoscopic-microscopic model and floor-field agent-based simulation. Written by an invited panel of experts, this book addresses students, engineers, and scholars, as well as anyone who needs a state-of-the-art overview of transport simulation today.

Probabilistic Machine Learning
Probabilistic Machine Learning

Author: Kevin P. Murphy

Publisher: MIT Press

Published: 2023-08-15

Total Pages: 1352

ISBN-13: 0262376008

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An advanced book for researchers and graduate students working in machine learning and statistics who want to learn about deep learning, Bayesian inference, generative models, and decision making under uncertainty. An advanced counterpart to Probabilistic Machine Learning: An Introduction, this high-level textbook provides researchers and graduate students detailed coverage of cutting-edge topics in machine learning, including deep generative modeling, graphical models, Bayesian inference, reinforcement learning, and causality. This volume puts deep learning into a larger statistical context and unifies approaches based on deep learning with ones based on probabilistic modeling and inference. With contributions from top scientists and domain experts from places such as Google, DeepMind, Amazon, Purdue University, NYU, and the University of Washington, this rigorous book is essential to understanding the vital issues in machine learning. Covers generation of high dimensional outputs, such as images, text, and graphs Discusses methods for discovering insights about data, based on latent variable models Considers training and testing under different distributions Explores how to use probabilistic models and inference for causal inference and decision making Features online Python code accompaniment

Topical Directions of Informatics
Topical Directions of Informatics

Author: Ivan V. Sergienko

Publisher: Springer Science & Business Media

Published: 2014-04-01

Total Pages: 309

ISBN-13: 1493904760

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This work is devoted to the late Ukrainian computer scientist V. M. Glushkov on the 90th anniversary of his birthday. Dr. Glushkov is known for his contribution to the world computer science and technology and this volume analyzes the ideas and paths of development of informatics formulated by him and demonstrate their important role in constructing computer technologies of basic research in the fields of applied mathematics, theories of computer programming and computing systems. A significant portion of the monograph is devoted to the elucidation of new results obtained in the field of mathematical modeling of complicated processes, creation of new methods for solving and investigating optimization problems in different statements and development of computer technologies for investigations in the field of economy, biology, medicine and information security in systems. The monograph will be of particular interest to informatics specialists and experts using methods of informatics and computer technologies to investigate complicated processes of different natures and developing new information technologies. It may also be useful for both graduate students and postgraduates specializing in Computer Science.

Methods of Optimization and Systems Analysis for Problems of Transcomputational Complexity
Methods of Optimization and Systems Analysis for Problems of Transcomputational Complexity

Author: Ivan V. Sergienko

Publisher: Springer Science & Business Media

Published: 2012-07-27

Total Pages: 237

ISBN-13: 1461442117

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This work presents lines of investigation and scientific achievements of the Ukrainian school of optimization theory and adjacent disciplines. These include the development of approaches to mathematical theories, methodologies, methods, and application systems for the solution of applied problems in economy, finances, energy saving, agriculture, biology, genetics, environmental protection, hardware and software engineering, information protection, decision making, pattern recognition, self-adapting control of complicated objects, personnel training, etc. The methods developed include sequential analysis of variants, nondifferential optimization, stochastic optimization, discrete optimization, mathematical modeling, econometric modeling, solution of extremum problems on graphs, construction of discrete images and combinatorial recognition, etc. Some of these methods became well known in the world's mathematical community and are now known as classic methods.

Computational Optimal Transport
Computational Optimal Transport

Author: Gabriel Peyre

Publisher: Foundations and Trends(r) in M

Published: 2019-02-12

Total Pages: 272

ISBN-13: 9781680835502

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The goal of Optimal Transport (OT) is to define geometric tools that are useful to compare probability distributions. Their use dates back to 1781. Recent years have witnessed a new revolution in the spread of OT, thanks to the emergence of approximate solvers that can scale to sizes and dimensions that are relevant to data sciences. Thanks to this newfound scalability, OT is being increasingly used to unlock various problems in imaging sciences (such as color or texture processing), computer vision and graphics (for shape manipulation) or machine learning (for regression, classification and density fitting). This monograph reviews OT with a bias toward numerical methods and their applications in data sciences, and sheds lights on the theoretical properties of OT that make it particularly useful for some of these applications. Computational Optimal Transport presents an overview of the main theoretical insights that support the practical effectiveness of OT before explaining how to turn these insights into fast computational schemes. Written for readers at all levels, the authors provide descriptions of foundational theory at two-levels. Generally accessible to all readers, more advanced readers can read the specially identified more general mathematical expositions of optimal transport tailored for discrete measures. Furthermore, several chapters deal with the interplay between continuous and discrete measures, and are thus targeting a more mathematically-inclined audience. This monograph will be a valuable reference for researchers and students wishing to get a thorough understanding of Computational Optimal Transport, a mathematical gem at the interface of probability, analysis and optimization.