Multi Stage Adjustable Robust Mixed Integer Optimization Via Iterative Splitting Of The Uncertainty Set
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Robust Optimization
| Author | : Aharon Ben-Tal |
| Publisher | : Princeton University Press |
| Total Pages | : 565 |
| Release | : 2009-08-10 |
| Genre | : Mathematics |
| ISBN | : 1400831059 |
Robust optimization is still a relatively new approach to optimization problems affected by uncertainty, but it has already proved so useful in real applications that it is difficult to tackle such problems today without considering this powerful methodology. Written by the principal developers of robust optimization, and describing the main achievements of a decade of research, this is the first book to provide a comprehensive and up-to-date account of the subject. Robust optimization is designed to meet some major challenges associated with uncertainty-affected optimization problems: to operate under lack of full information on the nature of uncertainty; to model the problem in a form that can be solved efficiently; and to provide guarantees about the performance of the solution. The book starts with a relatively simple treatment of uncertain linear programming, proceeding with a deep analysis of the interconnections between the construction of appropriate uncertainty sets and the classical chance constraints (probabilistic) approach. It then develops the robust optimization theory for uncertain conic quadratic and semidefinite optimization problems and dynamic (multistage) problems. The theory is supported by numerous examples and computational illustrations. An essential book for anyone working on optimization and decision making under uncertainty, Robust Optimization also makes an ideal graduate textbook on the subject.
Emerging Frontiers in Industrial and Systems Engineering
| Author | : Harriet B. Nembhard |
| Publisher | : CRC Press |
| Total Pages | : 354 |
| Release | : 2019-06-13 |
| Genre | : Technology & Engineering |
| ISBN | : 0429947712 |
Success is driven through collaboration. The field of Industrial and Systems Engineering has evolved as a major engineering field with interdisciplinary strength drawn from effective utilization, process improvement, optimization, design, and management of complex systems. It is a broad discipline that is important to nearly every attempt to solve problems facing the needs of society and the welfare of humanity. In order to carry this forward, successful collaborations are needed between industry, government, and academia. This book brings together an international group of distinguished practitioners and academics in manufacturing, healthcare, logistics, and energy sectors to examine what enables successful collaborations. The book is divided into two key parts: 1) partnerships, frameworks, and leadership; and 2) engineering applications and case studies. Part I highlights some of the ways partnerships emerge between those seeking to innovate and educate in industrial and systems engineering, some useful frameworks and methodologies, as well as some of the ideas and practices that undergird leadership in the profession. Part II provides case studies and applications to illustrate the power of the partnerships between academia and practice in industrial and systems engineering. Features Examines the success from multiple industries Provides frameworks for building teams and avoiding pitfalls Contains international perspectives of success Uses collaborative approaches from industry, government, and academia Includes real world case studies illustrating the enabling factors Offers engineering education and student-centric takeaways
Advances and Trends in Optimization with Engineering Applications
| Author | : Tamas Terlaky |
| Publisher | : SIAM |
| Total Pages | : 730 |
| Release | : 2017-04-26 |
| Genre | : Mathematics |
| ISBN | : 1611974682 |
Optimization is of critical importance in engineering. Engineers constantly strive for the best possible solutions, the most economical use of limited resources, and the greatest efficiency. As system complexity increases, these goals mandate the use of state-of-the-art optimization techniques. In recent years, the theory and methodology of optimization have seen revolutionary improvements. Moreover, the exponential growth in computational power, along with the availability of multicore computing with virtually unlimited memory and storage capacity, has fundamentally changed what engineers can do to optimize their designs. This is a two-way process: engineers benefit from developments in optimization methodology, and challenging new classes of optimization problems arise from novel engineering applications. Advances and Trends in Optimization with Engineering Applications reviews 10 major areas of optimization and related engineering applications, providing a broad summary of state-of-the-art optimization techniques most important to engineering practice. Each part provides a clear overview of a specific area and discusses a range of real-world problems. The book provides a solid foundation for engineers and mathematical optimizers alike who want to understand the importance of optimization methods to engineering and the capabilities of these methods.
Multi-level Mixed-Integer Optimization
| Author | : Styliani Avraamidou |
| Publisher | : Walter de Gruyter GmbH & Co KG |
| Total Pages | : 139 |
| Release | : 2022-06-06 |
| Genre | : Technology & Engineering |
| ISBN | : 311076038X |
This book provides the fundamental underlying mathematical theory, numerical algorithms and effi cient computational tools for the solution of multi-level mixedinteger optimization problems. It can enable a vast array of decision makers and engineers (e.g. process engineers, bioengineers, chemical and civil engineers, and economists) to model, formulate and solve hierarchical decision making problems. The book gives detailed insights on multi-level optimization by comprehensive explanations, step-by-step numerical examples and case studies, plots, and diagrams.
Adversarial Risk Analysis
| Author | : David L. Banks |
| Publisher | : CRC Press |
| Total Pages | : 220 |
| Release | : 2015-06-30 |
| Genre | : Business & Economics |
| ISBN | : 1498712401 |
Winner of the 2017 De Groot Prize awarded by the International Society for Bayesian Analysis (ISBA)A relatively new area of research, adversarial risk analysis (ARA) informs decision making when there are intelligent opponents and uncertain outcomes. Adversarial Risk Analysis develops methods for allocating defensive or offensive resources against
Resource-Constrained Project Scheduling
| Author | : Christian Artigues |
| Publisher | : John Wiley & Sons |
| Total Pages | : 235 |
| Release | : 2013-03-01 |
| Genre | : Technology & Engineering |
| ISBN | : 1118623703 |
This title presents a large variety of models and algorithms dedicated to the resource-constrained project scheduling problem (RCPSP), which aims at scheduling at minimal duration a set of activities subject to precedence constraints and limited resource availabilities. In the first part, the standard variant of RCPSP is presented and analyzed as a combinatorial optimization problem. Constraint programming and integer linear programming formulations are given. Relaxations based on these formulations and also on related scheduling problems are presented. Exact methods and heuristics are surveyed. Computational experiments, aiming at providing an empirical insight on the difficulty of the problem, are provided. The second part of the book focuses on several other variants of the RCPSP and on their solution methods. Each variant takes account of real-life characteristics which are not considered in the standard version, such as possible interruptions of activities, production and consumption of resources, cost-based approaches and uncertainty considerations. The last part presents industrial case studies where the RCPSP plays a central part. Applications are presented in various domains such as assembly shop and rolling ingots production scheduling, project management in information technology companies and instruction scheduling for VLIW processor architectures.
Distributed Optimization and Statistical Learning Via the Alternating Direction Method of Multipliers
| Author | : Stephen Boyd |
| Publisher | : Now Publishers Inc |
| Total Pages | : 138 |
| Release | : 2011 |
| Genre | : Computers |
| ISBN | : 160198460X |
Surveys the theory and history of the alternating direction method of multipliers, and discusses its applications to a wide variety of statistical and machine learning problems of recent interest, including the lasso, sparse logistic regression, basis pursuit, covariance selection, support vector machines, and many others.
Mixed Integer Nonlinear Programming
| Author | : Jon Lee |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 687 |
| Release | : 2011-12-02 |
| Genre | : Mathematics |
| ISBN | : 1461419271 |
Many engineering, operations, and scientific applications include a mixture of discrete and continuous decision variables and nonlinear relationships involving the decision variables that have a pronounced effect on the set of feasible and optimal solutions. Mixed-integer nonlinear programming (MINLP) problems combine the numerical difficulties of handling nonlinear functions with the challenge of optimizing in the context of nonconvex functions and discrete variables. MINLP is one of the most flexible modeling paradigms available for optimization; but because its scope is so broad, in the most general cases it is hopelessly intractable. Nonetheless, an expanding body of researchers and practitioners — including chemical engineers, operations researchers, industrial engineers, mechanical engineers, economists, statisticians, computer scientists, operations managers, and mathematical programmers — are interested in solving large-scale MINLP instances.
