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Book Nonlinear Interval Optimization for Uncertain Problems

Download or read book Nonlinear Interval Optimization for Uncertain Problems written by Chao Jiang and published by Springer Nature. This book was released on 2020-12-08 with total page 291 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Book Applications of Nature Inspired Computing and Optimization Techniques

Download or read book Applications of Nature Inspired Computing and Optimization Techniques written by and published by Elsevier. This book was released on 2024-04-04 with total page 566 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Book Introduction to Nonlinear Optimization

Download or read book Introduction to Nonlinear Optimization written by David A. Wismer and published by North Holland. This book was released on 1978 with total page 424 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Advances in Mechanical Design

Download or read book Advances in Mechanical Design written by Jianrong Tan and published by Springer Nature. This book was released on with total page 2698 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Global Optimization Using Interval Analysis

Download or read book Global Optimization Using Interval Analysis written by Eldon Hansen and published by CRC Press. This book was released on 2003-12-19 with total page 528 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Book Neutrosophic Number Nonlinear Programming Problems and Their General Solution Methods under Neutrosophic Number Environments

Download or read book Neutrosophic Number Nonlinear Programming Problems and Their General Solution Methods under Neutrosophic Number Environments written by Jun Ye and published by Infinite Study. This book was released on with total page 10 pages. Available in PDF, EPUB and Kindle. Book excerpt: In practical situations, we often have to handle programming problems involving indeterminate information.

Book Soft Computing Approach for Mathematical Modeling of Engineering Problems

Download or read book Soft Computing Approach for Mathematical Modeling of Engineering Problems written by Ali Ahmadian and published by CRC Press. This book was released on 2021-09-02 with total page 160 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book describes different mathematical modeling and soft computing techniques used to solve practical engineering problems. It gives an overview of the current state of soft computing techniques and describes the advantages and disadvantages of soft computing compared to traditional hard computing techniques. Through examples and case studies, the editors demonstrate and describe how problems with inherent uncertainty can be addressed and eventually solved through the aid of numerical models and methods. The chapters address several applications and examples in bioengineering science, drug delivery, solving inventory issues, Industry 4.0, augmented reality and weather forecasting. Other examples include solving fuzzy-shortest-path problems by introducing a new distance and ranking functions. Because, in practice, problems arise with uncertain data and most of them cannot be solved exactly and easily, the main objective is to develop models that deliver solutions with the aid of numerical methods. This is the reason behind investigating soft numerical computing in dynamic systems. Having this in mind, the authors and editors have considered error of approximation and have discussed several common types of errors and their propagations. Moreover, they have explained the numerical methods, along with convergence and consistence properties and characteristics, as the main objectives behind this book involve considering, discussing and proving related theorems within the setting of soft computing. This book examines dynamic models, and how time is fundamental to the structure of the model and data as well as the understanding of how a process unfolds • Discusses mathematical modeling with soft computing and the implementations of uncertain mathematical models • Examines how uncertain dynamic systems models include uncertain state, uncertain state space and uncertain state’s transition functions • Assists readers to become familiar with many soft numerical methods to simulate the solution function’s behavior This book is intended for system specialists who are interested in dynamic systems that operate at different time scales. The book can be used by engineering students, researchers and professionals in control and finite element fields as well as all engineering, applied mathematics, economics and computer science interested in dynamic and uncertain systems. Ali Ahmadian is a Senior Lecturer at the Institute of IR 4.0, The National University of Malaysia. Soheil Salahshour is an associate professor at Bahcesehir University.

Book Neutrosophic Multi Criteria Decision Making

Download or read book Neutrosophic Multi Criteria Decision Making written by Florentin Smarandache and published by MDPI. This book was released on 2018-10-12 with total page 207 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a printed edition of the Special Issue "Neutrosophic Multi-Criteria Decision Making" that was published in Axioms

Book Affine Arithmetic Based Methods for Uncertain Power System Analysis

Download or read book Affine Arithmetic Based Methods for Uncertain Power System Analysis written by Alfredo Vaccaro and published by Elsevier. This book was released on 2022-04-07 with total page 166 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Book Handbook of Research on Natural Computing for Optimization Problems

Download or read book Handbook of Research on Natural Computing for Optimization Problems written by Mandal, Jyotsna Kumar and published by IGI Global. This book was released on 2016-05-25 with total page 1015 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Book Optimization of Complex Systems  Theory  Models  Algorithms and Applications

Download or read book Optimization of Complex Systems Theory Models Algorithms and Applications written by Hoai An Le Thi and published by Springer. This book was released on 2019-06-15 with total page 1164 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contains 112 papers selected from about 250 submissions to the 6th World Congress on Global Optimization (WCGO 2019) which takes place on July 8–10, 2019 at University of Lorraine, Metz, France. The book covers both theoretical and algorithmic aspects of Nonconvex Optimization, as well as its applications to modeling and solving decision problems in various domains. It is composed of 10 parts, each of them deals with either the theory and/or methods in a branch of optimization such as Continuous optimization, DC Programming and DCA, Discrete optimization & Network optimization, Multiobjective programming, Optimization under uncertainty, or models and optimization methods in a specific application area including Data science, Economics & Finance, Energy & Water management, Engineering systems, Transportation, Logistics, Resource allocation & Production management. The researchers and practitioners working in Nonconvex Optimization and several application areas can find here many inspiring ideas and useful tools & techniques for their works.

Book Power System Operation with Large Scale Stochastic Wind Power Integration

Download or read book Power System Operation with Large Scale Stochastic Wind Power Integration written by Tao Ding and published by Springer. This book was released on 2016-09-17 with total page 217 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book addresses the uncertainties of wind power modeled as interval numbers and assesses the physical modeling and methods for interval power flow, interval economic dispatch and interval robust economic dispatch. In particular, the optimization models are set up to address these topics and the state-of-the-art methods are employed to efficiently solve the proposed models. Several standard IEEE test systems as well as real-world large-scale Polish power systems have been tested to verify the effectiveness of the proposed models and methods. These methods can be further applied to other research fields that are involved with uncertainty.

Book Modern Trends in Structural and Solid Mechanics 3

Download or read book Modern Trends in Structural and Solid Mechanics 3 written by Noel Challamel and published by John Wiley & Sons. This book was released on 2021-06-02 with total page 306 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book comprised of three separate volumes presents the recent developments and research discoveries in structural and solid mechanics; it is dedicated to Professor Isaac Elishakoff. This third volume is devoted to non-deterministic mechanics. Modern Trends in Structural and Solid Mechanics 3 has broad scope, covering topics such: design optimization under uncertainty, interval field approaches, convex analysis, quantum inspired topology optimization and stochastic dynamics. The book is illustrated by many applications in the field of aerospace engineering, mechanical engineering, civil engineering, biomedical engineering and automotive engineering. This book is intended for graduate students and researchers in the field of theoretical and applied mechanics.

Book Proceedings of the 19th Asia Pacific Automotive Engineering Conference   SAE China Congress 2017  Selected Papers

Download or read book Proceedings of the 19th Asia Pacific Automotive Engineering Conference SAE China Congress 2017 Selected Papers written by Society of Automotive Engineers (SAE-China) and published by Springer. This book was released on 2018-10-06 with total page 1187 pages. Available in PDF, EPUB and Kindle. Book excerpt: This Proceedings volume gathers outstanding papers submitted to the 19th Asia Pacific Automotive Engineering Conference & 2017 SAE-China Congress, the majority of which are from China – the largest car-maker as well as most dynamic car market in the world. The book covers a wide range of automotive topics, presenting the latest technical advances and approaches to help technicians solve the practical problems that most affect their daily work.

Book Facets of Uncertainties and Applications

Download or read book Facets of Uncertainties and Applications written by Mihir K. Chakraborty and published by Springer. This book was released on 2015-05-11 with total page 343 pages. Available in PDF, EPUB and Kindle. Book excerpt: Since the emergence of the formal concept of probability theory in the seventeenth century, uncertainty has been perceived solely in terms of probability theory. However, this apparently unique link between uncertainty and probability theory has come under investigation a few decades back. Uncertainties are nowadays accepted to be of various kinds. Uncertainty in general could refer to different sense like not certainly known, questionable, problematic, vague, not definite or determined, ambiguous, liable to change, not reliable. In Indian languages, particularly in Sanskrit-based languages, there are other higher levels of uncertainties. It has been shown that several mathematical concepts such as the theory of fuzzy sets, theory of rough sets, evidence theory, possibility theory, theory of complex systems and complex network, theory of fuzzy measures and uncertainty theory can also successfully model uncertainty.

Book Information Processing and Management of Uncertainty in Knowledge Based Systems

Download or read book Information Processing and Management of Uncertainty in Knowledge Based Systems written by Marie-Jeanne Lesot and published by Springer Nature. This book was released on 2020-06-05 with total page 816 pages. Available in PDF, EPUB and Kindle. Book excerpt: This three volume set (CCIS 1237-1239) constitutes the proceedings of the 18th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU 2020, in June 2020. The conference was scheduled to take place in Lisbon, Portugal, at University of Lisbon, but due to COVID-19 pandemic it was held virtually. The 173 papers were carefully reviewed and selected from 213 submissions. The papers are organized in topical sections: homage to Enrique Ruspini; invited talks; foundations and mathematics; decision making, preferences and votes; optimization and uncertainty; games; real world applications; knowledge processing and creation; machine learning I; machine learning II; XAI; image processing; temporal data processing; text analysis and processing; fuzzy interval analysis; theoretical and applied aspects of imprecise probabilities; similarities in artificial intelligence; belief function theory and its applications; aggregation: theory and practice; aggregation: pre-aggregation functions and other generalizations of monotonicity; aggregation: aggregation of different data structures; fuzzy methods in data mining and knowledge discovery; computational intelligence for logistics and transportation problems; fuzzy implication functions; soft methods in statistics and data analysis; image understanding and explainable AI; fuzzy and generalized quantifier theory; mathematical methods towards dealing with uncertainty in applied sciences; statistical image processing and analysis, with applications in neuroimaging; interval uncertainty; discrete models and computational intelligence; current techniques to model, process and describe time series; mathematical fuzzy logic and graded reasoning models; formal concept analysis, rough sets, general operators and related topics; computational intelligence methods in information modelling, representation and processing.

Book Fuzzy Preference Ordering of Interval Numbers in Decision Problems

Download or read book Fuzzy Preference Ordering of Interval Numbers in Decision Problems written by Atanu Sengupta and published by Springer. This book was released on 2009-02-24 with total page 168 pages. Available in PDF, EPUB and Kindle. Book excerpt: In conventional mathematical programming, coefficients of problems are usually determined by the experts as crisp values in terms of classical mathematical reasoning. But in reality, in an imprecise and uncertain environment, it will be utmost unrealistic to assume that the knowledge and representation of an expert can come in a precise way. The wider objective of the book is to study different real decision situations where problems are defined in inexact environment. Inexactness are mainly generated in two ways – (1) due to imprecise perception and knowledge of the human expert followed by vague representation of knowledge as a DM; (2) due to huge-ness and complexity of relations and data structure in the definition of the problem situation. We use interval numbers to specify inexact or imprecise or uncertain data. Consequently, the study of a decision problem requires answering the following initial questions: How should we compare and define preference ordering between two intervals?, interpret and deal inequality relations involving interval coefficients?, interpret and make way towards the goal of the decision problem? The present research work consists of two closely related fields: approaches towards defining a generalized preference ordering scheme for interval attributes and approaches to deal with some issues having application potential in many areas of decision making.