Posted by **AvaxGenius** at May 31, 2020

English | PDF | 2010 | 218 Pages | ISBN : 0387886699 | 3.34 MB

This self-contained text provides a solid introduction to global and nonlinear optimization, providing students of mathematics and interdisciplinary sciences with a strong foundation in applied optimization techniques. The book offers a unique hands-on and critical approach to applied optimization which includes the presentation of numerous algorithms, examples, and illustrations, designed to improve the reader’s intuition and develop the analytical skills needed to identify optimization problems, classify the structure of a model, and determine whether a solution fulfills optimality conditions.

Posted by **step778** at March 7, 2019

2010 | pages: 214 | ISBN: 0387886699 | PDF | 2,1 mb

Posted by **AvaxGenius** at March 1, 2024

English | PDF | 2002 | 492 Pages | ISBN : 1402010311 | 32.8 MB

Interest in constrained optimization originated with the simple linear pro gramming model since it was practical and perhaps the only computationally tractable model at the time. Constrained linear optimization models were soon adopted in numerous application areas and are perhaps the most widely used mathematical models in operations research and management science at the time of this writing. Modelers have, however, found the assumption of linearity to be overly restrictive in expressing the real-world phenomena and problems in economics, finance, business, communication, engineering design, computational biology, and other areas that frequently demand the use of nonlinear expressions and discrete variables in optimization models.

Posted by **AvaxGenius** at April 5, 2020

English | PDF | 1997 | 394 Pages | ISBN : 0792343271 | 23.92 MB

Bayesian decision theory is known to provide an effective framework for the practical solution of discrete and nonconvex optimization problems. This book is the first to demonstrate that this framework is also well suited for the exploitation of heuristic methods in the solution of such problems, especially those of large scale for which exact optimization approaches can be prohibitively costly. The book covers all aspects ranging from the formal presentation of the Bayesian Approach, to its extension to the Bayesian Heuristic Strategy, and its utilization within the informal, interactive Dynamic Visualization strategy.

Posted by **insetes** at Feb. 21, 2019

2002 | 478 Pages | ISBN: 1441952357 | PDF | 15 MB

Posted by **hill0** at Feb. 27, 2021

by Themistocles M. Rassias

English | 2021 | ISBN: 3030617319 | 495 Pages | PDF EPUB | 39 MB

Posted by **AvaxGenius** at July 4, 2021

English | PDF | 2006 | 559 Pages | ISBN : 0387304088 | 27.8 MB

Optimization models based on a nonlinear systems description often possess multiple local optima. The objective of Global Optimization (GO) is to find the best possible solution of multiextremal problems. This volume illustrates the applicability of GO modeling techniques and solution strategies to real-world problems. Coverage extends to a broad range of applications, from agroecosystem management to robot design. Proposed solutions encompass a range of practical and viable methods.

Posted by **arundhati** at Feb. 24, 2021

English | ISBN: 0387757139 | 2009 | 548 pages | PDF | 11 MB

Posted by **AvaxGenius** at Nov. 1, 2020

English | EPUB | 2020 | 379 Pages | ISBN : 3030554031 | 20.8 MB

Intended for advanced undergraduate/graduate students as well as scientists and engineers, this textbook presents a multi-disciplinary view of optimization, providing a thorough examination of algorithms, methods, techniques, and tools from diverse areas of optimization.

Posted by **step778** at March 2, 2020

English | 2015 | pages: 522 | ISBN: 3319345192 | PDF | 8,2 mb