04068nam 22006135 450 991025428100332120251113181408.01-4939-7199-910.1007/978-1-4939-7199-2(CKB)3710000001405836(DE-He213)978-1-4939-7199-2(MiAaPQ)EBC4880091(PPN)202988635(EXLCZ)99371000000140583620170617d2017 u| 0engurnn#008mamaatxtrdacontentcrdamediacrrdacarrierDeterministic Global Optimization An Introduction to the Diagonal Approach /by Yaroslav D. Sergeyev, Dmitri E. Kvasov1st ed. 2017.New York, NY :Springer New York :Imprint: Springer,2017.1 online resource (X, 136 p. 39 illus.)SpringerBriefs in Optimization,2191-575X1-4939-7197-2 Includes bibliographical references.1. Lipschitz global optimization -- 2. One-dimensional algorithms and their accleration -- 3. Diagonal approach and efficient paritioning strategies -- 4. Global optimization algorithms based on the non-redundant partitions -- References.This book begins with a concentrated introduction into deterministic global optimization and moves forward to present new original results from the authors who are well known experts in the field. Multiextremal continuous problems that have an unknown structure with Lipschitz objective functions and functions having the first Lipschitz derivatives defined over hyperintervals are examined. A class of algorithms using several Lipschitz constants is introduced which has its origins in the DIRECT (DIviding RECTangles) method. This new class is based on an efficient strategy that is applied for the search domain partitioning. In addition a survey on derivative free methods and methods using the first derivatives is given for both one-dimensional and multi-dimensional cases. Non-smooth and smooth minorants and acceleration techniques that can speed up several classes of global optimization methods with examples of applications and problems arising in numerical testing of global optimizationalgorithms are discussed. Theoretical considerations are illustrated through engineering applications. Extensive numerical testing of algorithms described in this book stretches the likelihood of establishing a link between mathematicians and practitioners. The authors conclude by describing applications and a generator of random classes of test functions with known local and global minima that is used in more than 40 countries of the world. This title serves as a starting point for students, researchers, engineers, and other professionals in operations research, management science, computer science, engineering, economics, environmental sciences, industrial and applied mathematics to obtain an overview of deterministic global optimization.   .SpringerBriefs in Optimization,2191-575XComputer programmingMathematical optimizationComputer scienceMathematicsProgramming TechniquesOptimizationMathematics of ComputingMathematical Applications in Computer ScienceComputer programming.Mathematical optimization.Computer scienceMathematics.Programming Techniques.Optimization.Mathematics of Computing.Mathematical Applications in Computer Science.519.3Sergeyev Yaroslav Dauthttp://id.loc.gov/vocabulary/relators/aut724332Kvasov Dmitri Eauthttp://id.loc.gov/vocabulary/relators/autMiAaPQMiAaPQMiAaPQBOOK9910254281003321Deterministic Global Optimization2266032UNINA