Ranking And Optimization Methodologies
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| Author | : Kathryn A. Zimmerman |
| Publisher | : Transportation Research Board |
| Total Pages | : 108 |
| Release | : 1995 |
| Genre | : Technology & Engineering |
| ISBN | : 9780309058667 |
This synthesis will be of interest to highway administrators; pavement management system (PMS), maintenance, and computer engineers; and technologists involved with data collection and computer programming for the purposes of a PMS. This synthesis describes the state of the practice with respect to pavement management methodologies to select projects and recommend preservation treatments. This report of the Transportation Research Board also describes the predominant pavement management methodologies being used by U.S. state and Canadian provincial transportation agencies; provides a general description of each methodology; and summarizes the requirements, benefits, hindrances, and constraints associated with each. It includes a review of domestic literature and a survey of current practices in North America. In addition, case studies are included to illustrate the use of these methodologies within transportation agencies. Operational and soon-to-be implemented technologies are also discussed, and an extensive bibliography is provided for further reference.
| Author | : Gade Pandu Rangaiah |
| Publisher | : World Scientific |
| Total Pages | : 454 |
| Release | : 2009 |
| Genre | : Technology & Engineering |
| ISBN | : 9812836527 |
Optimization has been playing a key role in the design, planning and operation of chemical and related processes for nearly half a century. Although process optimization for multiple objectives was studied by several researchers back in the 1970s and 1980s, it has attracted active research in the last 10 years, spurred by the new and effective techniques for multi-objective optimization. In order to capture this renewed interest, this monograph presents the recent and ongoing research in multi-optimization techniques and their applications in chemical engineering. Following a brief introduction and general review on the development of multi-objective optimization applications in chemical engineering since 2000, the book gives a description of selected multi-objective techniques and then goes on to discuss chemical engineering applications. These applications are from diverse areas within chemical engineering, and are presented in detail. All chapters will be of interest to researchers in multi-objective optimization and/or chemical engineering; they can be read individually and used in one''s learning and research. Several exercises are included at the end of many chapters, for use by both practicing engineers and students.
| Author | : Xin-She Yang |
| Publisher | : John Wiley & Sons |
| Total Pages | : 384 |
| Release | : 2018-09-19 |
| Genre | : Mathematics |
| ISBN | : 1119490545 |
A guide to modern optimization applications and techniques in newly emerging areas spanning optimization, data science, machine intelligence, engineering, and computer sciences Optimization Techniques and Applications with Examples introduces the fundamentals of all the commonly used techniques in optimization that encompass the broadness and diversity of the methods (traditional and new) and algorithms. The author—a noted expert in the field—covers a wide range of topics including mathematical foundations, optimization formulation, optimality conditions, algorithmic complexity, linear programming, convex optimization, and integer programming. In addition, the book discusses artificial neural network, clustering and classifications, constraint-handling, queueing theory, support vector machine and multi-objective optimization, evolutionary computation, nature-inspired algorithms and many other topics. Designed as a practical resource, all topics are explained in detail with step-by-step examples to show how each method works. The book’s exercises test the acquired knowledge that can be potentially applied to real problem solving. By taking an informal approach to the subject, the author helps readers to rapidly acquire the basic knowledge in optimization, operational research, and applied data mining. This important resource: Offers an accessible and state-of-the-art introduction to the main optimization techniques Contains both traditional optimization techniques and the most current algorithms and swarm intelligence-based techniques Presents a balance of theory, algorithms, and implementation Includes more than 100 worked examples with step-by-step explanations Written for upper undergraduates and graduates in a standard course on optimization, operations research and data mining, Optimization Techniques and Applications with Examples is a highly accessible guide to understanding the fundamentals of all the commonly used techniques in optimization.
| Author | : K.S. Tang |
| Publisher | : CRC Press |
| Total Pages | : 283 |
| Release | : 2018-09-03 |
| Genre | : Science |
| ISBN | : 1351832522 |
The first book to focus on jumping genes outside bioscience and medicine, Multiobjective Optimization Methodology: A Jumping Gene Approach introduces jumping gene algorithms designed to supply adequate, viable solutions to multiobjective problems quickly and with low computational cost. Better Convergence and a Wider Spread of Nondominated Solutions The book begins with a thorough review of state-of-the-art multiobjective optimization techniques. For readers who may not be familiar with the bioscience behind the jumping gene, it then outlines the basic biological gene transposition process and explains the translation of the copy-and-paste and cut-and-paste operations into a computable language. To justify the scientific standing of the jumping genes algorithms, the book provides rigorous mathematical derivations of the jumping genes operations based on schema theory. It also discusses a number of convergence and diversity performance metrics for measuring the usefulness of the algorithms. Practical Applications of Jumping Gene Algorithms Three practical engineering applications showcase the effectiveness of the jumping gene algorithms in terms of the crucial trade-off between convergence and diversity. The examples deal with the placement of radio-to-fiber repeaters in wireless local-loop systems, the management of resources in WCDMA systems, and the placement of base stations in wireless local-area networks. Offering insight into multiobjective optimization, the authors show how jumping gene algorithms are a useful addition to existing evolutionary algorithms, particularly to obtain quick convergence solutions and solutions to outliers.
| Author | : De-Shuang Huang |
| Publisher | : Springer |
| Total Pages | : 781 |
| Release | : 2017-07-20 |
| Genre | : Computers |
| ISBN | : 3319633155 |
This three-volume set LNCS 10361, LNCS 10362, and LNAI 10363 constitutes the refereed proceedings of the 13th International Conference on Intelligent Computing, ICIC 2017, held in Liverpool, UK, in August 2017. The 212 full papers and 20 short papers of the three proceedings volumes were carefully reviewed and selected from 612 submissions. This third volume of the set comprises 67 papers. The papers are organized in topical sections such as Intelligent Computing in Robotics; Intelligent Computing in Computer Vision; Intelligent Control and Automation; Intelligent Agent and Web Applications; Fuzzy Theory and Algorithms; Supervised Learning; Unsupervised Learning; Kernel Methods and Supporting Vector Machines; Knowledge Discovery and Data Mining; Natural Language Processing and Computational Linguistics; Advances of Soft Computing: Algorithms and Its Applications - Rozaida Ghazali; Advances in Swarm Intelligence Algorithm; Computational Intelligence and Security for Image Applications in SocialNetwork; Biomedical Image Analysis; Information Security; Machine Learning; Intelligent Data Analysis and Prediction.
| Author | : Tilahun, Surafel Luleseged |
| Publisher | : IGI Global |
| Total Pages | : 327 |
| Release | : 2018-06-22 |
| Genre | : Computers |
| ISBN | : 1522550925 |
When it comes to optimization techniques, in some cases, the available information from real models may not be enough to construct either a probability distribution or a membership function for problem solving. In such cases, there are various theories that can be used to quantify the uncertain aspects. Optimization Techniques for Problem Solving in Uncertainty is a scholarly reference resource that looks at uncertain aspects involved in different disciplines and applications. Featuring coverage on a wide range of topics including uncertain preference, fuzzy multilevel programming, and metaheuristic applications, this book is geared towards engineers, managers, researchers, and post-graduate students seeking emerging research in the field of optimization.
| Author | : Anita Khosla |
| Publisher | : John Wiley & Sons |
| Total Pages | : 548 |
| Release | : 2023-04-26 |
| Genre | : Computers |
| ISBN | : 1119906377 |
OPTIMIZATION TECHNIQUES IN ENGINEERING The book describes the basic components of an optimization problem along with the formulation of design problems as mathematical programming problems using an objective function that expresses the main aim of the model, and how it is to be either minimized or maximized; subsequently, the concept of optimization and its relevance towards an optimal solution in engineering applications, is explained. This book aims to present some of the recent developments in the area of optimization theory, methods, and applications in engineering. It focuses on the metaphor of the inspired system and how to configure and apply the various algorithms. The book comprises 30 chapters and is organized into two parts: Part I — Soft Computing and Evolutionary-Based Optimization; and Part II — Decision Science and Simulation-Based Optimization, which contains application-based chapters. Readers and users will find in the book: An overview and brief background of optimization methods which are used very popularly in almost all applications of science, engineering, technology, and mathematics; An in-depth treatment of contributions to optimal learning and optimizing engineering systems; Maps out the relations between optimization and other mathematical topics and disciplines; A problem-solving approach and a large number of illustrative examples, leading to a step-by-step formulation and solving of optimization problems. Audience Researchers, industry professionals, academicians, and doctoral scholars in major domains of engineering, production, thermal, electrical, industrial, materials, design, computer engineering, and natural sciences. The book is also suitable for researchers and postgraduate students in mathematics, applied mathematics, and industrial mathematics.
| Author | : Juan Miguel Lujano Rojas |
| Publisher | : Elsevier |
| Total Pages | : 352 |
| Release | : 2022-09-28 |
| Genre | : Technology & Engineering |
| ISBN | : 012824206X |
Genetic Optimization Techniques for Sizing and Management of Modern Power Systems explores the design and management of energy systems using a genetic algorithm as the primary optimization technique. Coverage ranges across topics related to resource estimation and energy systems simulation. Chapters address the integration of distributed generation, the management of electric vehicle charging, and microgrid dimensioning for resilience enhancement with detailed discussion and solutions using parallel genetic algorithms. The work is suitable for researchers and practitioners working in power systems optimization requiring information for systems planning purposes, seeking knowledge on mathematical models available for simulation and assessment, and relevant applications in energy policy. - Presents a range of essential techniques for using genetic algorithms in power system analysis, includingeconomic dispatch, forecasting, and optimal power fl ow, among other topics. - Addresses relevant optimization problems, such as neural network training and clustering analysis, usinggenetic algorithms. - Discusses clearly and straightforwardly the implementation of genetic algorithms and its combination withother heuristic techniques. - Describes the iHOGA® and MHOGA® commercial tools, which utilize genetic algorithms for designingand managing energy systems based on renewable energies.
| Author | : Vinod Kumar |
| Publisher | : Bentham Science Publishers |
| Total Pages | : 167 |
| Release | : 2024-05-22 |
| Genre | : Computers |
| ISBN | : 9815196332 |
Optimization Techniques for Decision-making and Information Security is a scholarly compilation that has been edited by experts with specialized knowledge in the fields of decision theory and cybersecurity. Through the synthesis of an extensive array of information, this edited volume presents novel methodologies and approaches that forge a link between the critical domain of information security and the realm of decision-making processes. The publication commences with a fundamental investigation that establishes the theoretical foundations of information security-relevant decision-making models. The subsequent chapters present comprehensive evaluations of real-world applications, showcasing an assortment of optimization techniques. The book offers a wide range of perspectives on the practical implementation of data analysis in various domains, including but not limited to power generation and optimization, solid transportation problems, soft computing techniques, wireless sensor networks, parametric set-valued optimization problems, data aggregation optimization techniques, fuzzy linear programming problems, and nonlinear chaotic systems. The anthology concludes with a comprehensive summary of the most noteworthy observations and ramifications extracted from the projects of all contributors. Key features - Presents a wide variety of sophisticated optimization methodologies - Explores the intricate intersection of decision theory and the safeguarding of confidential information. - Emphasizes effectiveness in improving decision-making processes designed to strengthen information security measures. - Showcases practical examples in different industrial domains through case studies and real-world problems. - Provides guidance and contemplations on strengthening information security environments. - Includes scientific references for advanced reading This book serves as an essential reference for policymakers, researchers, and professionals who are learning about or working in information security roles.
| Author | : Mykel J. Kochenderfer |
| Publisher | : MIT Press |
| Total Pages | : 521 |
| Release | : 2019-03-12 |
| Genre | : Computers |
| ISBN | : 0262039427 |
A comprehensive introduction to optimization with a focus on practical algorithms for the design of engineering systems. This book offers a comprehensive introduction to optimization with a focus on practical algorithms. The book approaches optimization from an engineering perspective, where the objective is to design a system that optimizes a set of metrics subject to constraints. Readers will learn about computational approaches for a range of challenges, including searching high-dimensional spaces, handling problems where there are multiple competing objectives, and accommodating uncertainty in the metrics. Figures, examples, and exercises convey the intuition behind the mathematical approaches. The text provides concrete implementations in the Julia programming language. Topics covered include derivatives and their generalization to multiple dimensions; local descent and first- and second-order methods that inform local descent; stochastic methods, which introduce randomness into the optimization process; linear constrained optimization, when both the objective function and the constraints are linear; surrogate models, probabilistic surrogate models, and using probabilistic surrogate models to guide optimization; optimization under uncertainty; uncertainty propagation; expression optimization; and multidisciplinary design optimization. Appendixes offer an introduction to the Julia language, test functions for evaluating algorithm performance, and mathematical concepts used in the derivation and analysis of the optimization methods discussed in the text. The book can be used by advanced undergraduates and graduate students in mathematics, statistics, computer science, any engineering field, (including electrical engineering and aerospace engineering), and operations research, and as a reference for professionals.
