Nonlinear Interval Optimization For Uncertain Problems
Download Nonlinear Interval Optimization For Uncertain Problems full books in PDF, epub, and Kindle. Read online free Nonlinear Interval Optimization For Uncertain Problems ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!
| Author | : Chao Jiang |
| Publisher | : Springer Nature |
| Total Pages | : 291 |
| Release | : 2020-12-08 |
| Genre | : Mathematics |
| ISBN | : 9811585466 |
This book systematically discusses nonlinear interval optimization design theory and methods. Firstly, adopting a mathematical programming theory perspective, it develops an innovative mathematical transformation model to deal with general nonlinear interval uncertain optimization problems, which is able to equivalently convert complex interval uncertain optimization problems to simple deterministic optimization problems. This model is then used as the basis for various interval uncertain optimization algorithms for engineering applications, which address the low efficiency caused by double-layer nested optimization. Further, the book extends the nonlinear interval optimization theory to design problems associated with multiple optimization objectives, multiple disciplines, and parameter dependence, and establishes the corresponding interval optimization models and solution algorithms. Lastly, it uses the proposed interval uncertain optimization models and methods to deal with practical problems in mechanical engineering and related fields, demonstrating the effectiveness of the models and methods.
| Author | : |
| Publisher | : Elsevier |
| Total Pages | : 566 |
| Release | : 2024-04-04 |
| Genre | : Mathematics |
| ISBN | : 0323957692 |
Advances in Computers, Volume 135 highlights advances in the field, with this new volume, Applications of Nature-inspired Computing and Optimization Techniques presenting interesting chapters on a variety of timely topics, including A Brief Introduction to Nature-inspired Computing, Optimization and Applications, Overview of Non-linear Interval Optimization Problems, Solving the Aircraft Landing Problem using the Bee Colony Optimization (BCO) Algorithm, Situation-based Genetic Network Programming to Solve Agent Control Problems, Small Signal Stability Enhancement of Large Interconnected Power System using Grasshopper Optimization Algorithm Tuned Power System Stabilizer, Air Quality Modelling for Smart Cities of India by Nature Inspired AI – A Sustainable Approach, and much more.Other sections cover Genetic Algorithm for the Optimization of Infectiological Parameter Values under Different Nutritional Status, A Novel Influencer Mutation Strategy for Nature-inspired Optimization Algorithms to Solve Electricity Price Forecasting Problem, Recent Trends in Human and Bio Inspired Computing: Use Case Study from Retail Perspective, Domain Knowledge Enriched Summarization of Legal Judgment Documents via Grey Wolf Optimization, and a host of other topics. - Includes algorithm specific studies that cover basic introduction and analysis of key components of algorithms, such as convergence, solution accuracy, computational costs, tuning, and control of parameters - Comprises some of the major applications of different domains - Presents application specific studies, incorporating ways of designing objective functions, solution representation, and constraint handling
| Author | : Jianrong Tan |
| Publisher | : Springer Nature |
| Total Pages | : 2698 |
| Release | : |
| Genre | : |
| ISBN | : 9819709229 |
| Author | : Jun Ye |
| Publisher | : Infinite Study |
| Total Pages | : 10 |
| Release | : |
| Genre | : |
| ISBN | : |
In practical situations, we often have to handle programming problems involving indeterminate information.
| Author | : Chao Jiang |
| Publisher | : |
| Total Pages | : 0 |
| Release | : 2021 |
| Genre | : |
| ISBN | : 9789811585470 |
This book systematically discusses nonlinear interval optimization design theory and methods. Firstly, adopting a mathematical programming theory perspective, it develops an innovative mathematical transformation model to deal with general nonlinear interval uncertain optimization problems, which is able to equivalently convert complex interval uncertain optimization problems to simple deterministic optimization problems. This model is then used as the basis for various interval uncertain optimization algorithms for engineering applications, which address the low efficiency caused by double-layer nested optimization. Further, the book extends the nonlinear interval optimization theory to design problems associated with multiple optimization objectives, multiple disciplines, and parameter dependence, and establishes the corresponding interval optimization models and solution algorithms. Lastly, it uses the proposed interval uncertain optimization models and methods to deal with practical problems in mechanical engineering and related fields, demonstrating the effectiveness of the models and methods.
| Author | : Florentin Smarandache |
| Publisher | : MDPI |
| Total Pages | : 207 |
| Release | : 2018-10-12 |
| Genre | : Mathematics |
| ISBN | : 3038972886 |
This book is a printed edition of the Special Issue "Neutrosophic Multi-Criteria Decision Making" that was published in Axioms
| Author | : Alfredo Vaccaro |
| Publisher | : Elsevier |
| Total Pages | : 166 |
| Release | : 2022-04-07 |
| Genre | : Technology & Engineering |
| ISBN | : 032390503X |
Affine Arithmetic-Based Methods for Uncertain Power System Analysis presents the unique properties and representative applications of Affine Arithmetic in power systems analysis, particularly as they are deployed for reliability optimization. The work provides a comprehensive foundation in Affine Arithmetic necessary to understand the central computing paradigms that can be adopted for uncertain power flow and optimal power flow analyses. These paradigms are adapted and applied to case studies, which integrate benchmark test systems and full step-by-step procedure for implementation so that readers are able to replicate and modify. The work is presented with illustrative numerical examples and MATLAB computations. - Provides a uniquely comprehensive review of affine arithmetic in both its core theoretical underpinnings and their developed applications to power system analysis - Details the exemplary benefits derived by the deployment of affine arithmetic methods for uncertainty handling in decision-making processes - Clarifies arithmetical complexity and eases the understanding of illustrative methodologies for researchers in both power system and decision-making fields
| Author | : Mandal, Jyotsna Kumar |
| Publisher | : IGI Global |
| Total Pages | : 1199 |
| Release | : 2016-05-25 |
| Genre | : Computers |
| ISBN | : 1522500596 |
Nature-inspired computation is an interdisciplinary topic area that connects the natural sciences to computer science. Since natural computing is utilized in a variety of disciplines, it is imperative to research its capabilities in solving optimization issues. The Handbook of Research on Natural Computing for Optimization Problems discusses nascent optimization procedures in nature-inspired computation and the innovative tools and techniques being utilized in the field. Highlighting empirical research and best practices concerning various optimization issues, this publication is a comprehensive reference for researchers, academicians, students, scientists, and technology developers interested in a multidisciplinary perspective on natural computational systems.
| Author | : Eldon Hansen |
| Publisher | : CRC Press |
| Total Pages | : 528 |
| Release | : 2003-12-19 |
| Genre | : Mathematics |
| ISBN | : 9780203026922 |
Employing a closed set-theoretic foundation for interval computations, Global Optimization Using Interval Analysis simplifies algorithm construction and increases generality of interval arithmetic. This Second Edition contains an up-to-date discussion of interval methods for solving systems of nonlinear equations and global optimization problems. It expands and improves various aspects of its forerunner and features significant new discussions, such as those on the use of consistency methods to enhance algorithm performance. Provided algorithms are guaranteed to find and bound all solutions to these problems despite bounded errors in data, in approximations, and from use of rounded arithmetic.
| Author | : Ram N. Mohapatra |
| Publisher | : Springer |
| Total Pages | : 366 |
| Release | : 2014-08-22 |
| Genre | : Mathematics |
| ISBN | : 813221952X |
This book discusses recent developments and contemporary research in mathematics, statistics and their applications in computing. All contributing authors are eminent academicians, scientists, researchers and scholars in their respective fields, hailing from around the world. The conference has emerged as a powerful forum, offering researchers a venue to discuss, interact and collaborate and stimulating the advancement of mathematics and its applications in computer science. The book will allow aspiring researchers to update their knowledge of cryptography, algebra, frame theory, optimizations, stochastic processes, compressive sensing, functional analysis, complex variables, etc. Educating future consumers, users, producers, developers and researchers in mathematics and computing is a challenging task and essential to the development of modern society. Hence, mathematics and its applications in computer science are of vital importance to a broad range of communities, including mathematicians and computing professionals across different educational levels and disciplines.
