Advances in Optimization and Approximation, Ding-Zhu Du; Jie Sun
Автор: Sundaram, Rangarajan K. Название: A First Course in Optimization Theory ISBN: 0521497701 ISBN-13(EAN): 9780521497701 Издательство: Cambridge Academ Рейтинг: Цена: 6811.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book, first published in 1996, introduces students to optimization theory and its use in economics and allied disciplines.
Автор: Mahmudov, Elimhan N Название: Approximation and Optimization of Discrete and Differential Inclu ISBN: 0323165400 ISBN-13(EAN): 9780323165402 Издательство: Elsevier Science Рейтинг: Цена: 18275.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Optimal control theory has numerous applications in both science and engineering. This book presents basic concepts and principles of mathematical programming in terms of set-valued analysis and develops a comprehensive optimality theory of problems described by ordinary and partial differential inclusions.
Автор: PARAMETRIC; BROSOWSKI; DEUTSCH Название: Parametric Optimization and Approximation ISBN: 3034862555 ISBN-13(EAN): 9783034862554 Издательство: Springer Рейтинг: Цена: 11179.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Автор: K. Glashoff; S.-A. Gustafson Название: Linear Optimization and Approximation ISBN: 0387908579 ISBN-13(EAN): 9780387908571 Издательство: Springer Рейтинг: Цена: 13275.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: A linear optimization problem is the task of minimizing a linear real-valued function of finitely many variables subject to linear con- straints;
Автор: Panos M. Pardalos Название: Approximation and Complexity in Numerical Optimization ISBN: 0792362756 ISBN-13(EAN): 9780792362753 Издательство: Springer Рейтинг: Цена: 41787.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Computational complexity, originating from the interactions between computer science and numerical optimization, is one of the major theories that have revolutionized the approach to solving optimization problems and to analyzing their intrinsic difficulty. This book deals with the themes of approximation and complexity.
Автор: Klaus Jansen; Stefano Leonardi; Vijay Vazirani Название: Approximation Algorithms for Combinatorial Optimization ISBN: 3540441867 ISBN-13(EAN): 9783540441861 Издательство: Springer Рейтинг: Цена: 9781.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Compiled from the proceedings of the 5th International Workshop on Approximation Algorithms for Combinatorial Optimization Problems, this volume contains 20 revised full papers. Coverage includes design and analysis of approximation algorithms, inapproximability results and online problems.
Автор: Marc Lassonde Название: Approximation, Optimization and Mathematical Economics ISBN: 379081363X ISBN-13(EAN): 9783790813630 Издательство: Springer Рейтинг: Цена: 16769.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The articles in this proceedings volume reflect the current trends in the theory of approximation, optimization and mathematical economics, and include numerous applications.
Описание: This cutting-edge volume presents recent advances in the area of metaheuristic combinatorial optimisation, with a special focus on evolutionary computation methods. Moreover, it addresses local search methods and hybrid approaches.
Автор: Patrick Siarry; Zbigniew Michalewicz Название: Advances in Metaheuristics for Hard Optimization ISBN: 3642092063 ISBN-13(EAN): 9783642092060 Издательство: Springer Рейтинг: Цена: 23058.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The editors, both leading experts in this field, have assembled a team of researchers to contribute 21 chapters organized into parts on simulated annealing, tabu search, ant colony algorithms, general purpose studies of evolutionary algorithms, applications of evolutionary algorithms, and metaheuristics.
Описание: Combinatorial optimisation is a ubiquitous discipline whose usefulness spans vast applications domains. This title presents advances in the area of metaheuristic combinatorial optimisation, with a focus on evolutionary computation methods. It addresses local search methods and hybrid approaches.
Combinational optimization (CO) is a topic in applied mathematics, decision science and computer science that consists of finding the best solution from a non-exhaustive search. CO is related to disciplines such as computational complexity theory and algorithm theory, and has important applications in fields such as operations research/management science, artificial intelligence, machine learning, and software engineering.
Advances in Combinatorial Optimization presents a generalized framework for formulating hard combinatorial optimization problems (COPs) as polynomial sized linear programs. Though developed based on the 'traveling salesman problem' (TSP), the framework allows for the formulating of many of the well-known NP-Complete COPs directly (without the need to reduce them to other COPs) as linear programs, and demonstrates the same for three other problems (e.g. the 'vertex coloring problem' (VCP)). This work also represents a proof of the equality of the complexity classes "P" (polynomial time) and "NP" (nondeterministic polynomial time), and makes a contribution to the theory and application of 'extended formulations' (EFs).
On a whole, Advances in Combinatorial Optimization offers new modeling and solution perspectives which will be useful to professionals, graduate students and researchers who are either involved in routing, scheduling and sequencing decision-making in particular, or in dealing with the theory of computing in general.
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