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Simulation-Based Optimization: Parametric Optimization Techniques and Reinforcement Learning introduce the evolving area of static and dynamic simulation-based optimization. Covered in detail are model-free optimization techniques – especially designed for those discrete-event, stochastic systems which can be simulated but whose analytical models are difficult to find in closed mathematical forms. Key features of this revised and improved Second Edition include: · Extensive coverage, via step-by-step recipes, of powerful new algorithms for static simulation optimization, including simultaneous perturbation, backtracking adaptive search and nested partitions, in addition to traditional met...
The book presents the select proceedings of the International Conference on Advancement in Manufacturing Engineering (ICAME) 2022 held at National Institute of Technology Delhi, India, during September 2–3, 2022. It discusses the latest research in the area of industrial and production engineering. Various topics covered in this book are precision engineering, additive manufacturing, computer-aided manufacturing, digital manufacturing, intelligent control systems and optimization, flexible manufacturing system, smart manufacturing, hybrid machining, smart materials, polymers, ceramics and composites and their processing, energy harvesting materials, design thinking and prototyping, product life cycle strategies, Industry 4.0, etc. The book is useful for researchers and professionals working in the area of industrial and production engineering.
Dedicated to the proper design, layout, and location of facilities, this definitive textbook outlines the main design and operational problems that occur in manufacturing and service systems, explains the significance of facility design and planning problems, and describes how mathematical models can be used to help analyze and solve them. Combining theory with practice, this revised textbook presents state-of-the-art topics in materials handling, warehousing, and logistics along with real-world examples that emphasize the importance of modeling and analysis when determining a solution to complex facility design problems. Facilities Design, Fifth Edition includes a balanced coverage of model...
The Handbook of Simulation Optimization presents an overview of the state of the art of simulation optimization, providing a survey of the most well-established approaches for optimizing stochastic simulation models and a sampling of recent research advances in theory and methodology. Leading contributors cover such topics as discrete optimization via simulation, ranking and selection, efficient simulation budget allocation, random search methods, response surface methodology, stochastic gradient estimation, stochastic approximation, sample average approximation, stochastic constraints, variance reduction techniques, model-based stochastic search methods and Markov decision processes. This single volume should serve as a reference for those already in the field and as a means for those new to the field for understanding and applying the main approaches. The intended audience includes researchers, practitioners and graduate students in the business/engineering fields of operations research, management science, operations management and stochastic control, as well as in economics/finance and computer science.
Simulation Methods for Reliability and Availability of Complex Systems discusses the use of computer simulation-based techniques and algorithms to determine reliability and availability (R and A) levels in complex systems. The book: shares theoretical or applied models and decision support systems that make use of simulation to estimate and to improve system R and A levels, forecasts emerging technologies and trends in the use of computer simulation for R and A and proposes hybrid approaches to the development of efficient methodologies designed to solve R and A-related problems in real-life systems. Dealing with practical issues, Simulation Methods for Reliability and Availability of Complex Systems is designed to support managers and system engineers in the improvement of R and A, as well as providing a thorough exploration of the techniques and algorithms available for researchers, and for advanced undergraduate and postgraduate students.
Rigorous treatment of the theory of deep learning from first principles, with applications to beautiful problems in the natural sciences.
In this provocative book, economist Jonathan Rothwell draws on the latest empirical evidence from across the social sciences to demonstrate how rich democracies have allowed racial politics and the interests of those at the top to subordinate justice. He looks at the rise of nationalism in Europe and the United States, revealing how this trend overlaps with racial prejudice and is related to mounting frustration with a political status quo that thrives on income inequality and inefficient markets. But economic differences are by no means inevitable. Differences in group status by race and ethnicity are dynamic and have reversed themselves across continents and within countries. Inequalities persist between races in the United States because Black Americans are denied equal access to markets and public services. Meanwhile, elite professional associations carve out privileged market status for their members, leading to compensation in excess of their skills.
There is significant debate regarding the quality of the national health system of the United States relative to those of other countries. The U.S. healthcare system has been heavily criticized as a highly inefficient, disorganized, fragmented, and under-resourced primary care system that contributes to high healthcare costs, high rates of uninsured individuals, and a number of health problems in comparison to the situation in other Western nations. Further, the United States is currently the only wealthy industrialized country that has not achieved universal health coverage. Together, these reasons help explain why important health indicators have been deteriorating recently. Assessing the ...
Proceedings of the Artificial Neural Networks in Engineering Conference, November 2002, St. Louis, Missouri. This annual conference publication presents refereed papers covering the following categories and their applications in the engineering domain: Neural Networks, Complex Systems, Evolutionary Programming, Data Mining, Fuzzy Logic, Adaptive Control, Pattern Recognition and Smart Engineering System Design. These papers are intended to provide a forum for researchers in the field to exchange ideas on smart engineering system design.