Sequential Approximate Multiobjective Optimization Using Computational Intelligence

Sequential Approximate Multiobjective Optimization Using Computational Intelligence PDF Author: Hirotaka Nakayama
Publisher: Springer Science & Business Media
ISBN: 3540889108
Category : Mathematics
Languages : en
Pages : 200

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Book Description
Many kinds of practical problems such as engineering design, industrial m- agement and ?nancial investment have multiple objectives con?icting with eachother. Thoseproblemscanbeformulatedasmultiobjectiveoptimization. In multiobjective optimization, there does not necessarily a unique solution which minimizes (or maximizes) all objective functions. We usually face to the situation in which if we want to improve some of objectives, we have to give up other objectives. Finally, we pay much attention on how much to improve some of objectives and instead how much to give up others. This is called “trade-o?. ” Note that making trade-o? is a problem of value ju- ment of decision makers. One of main themes of multiobjective optimization is how to incorporate value judgment of decision makers into decision s- port systems. There are two major issues in value judgment (1) multiplicity of value judgment and (2) dynamics of value judgment. The multiplicity of value judgment is treated as trade-o? analysis in multiobjective optimi- tion. On the other hand, dynamics of value judgment is di?cult to treat. However, it is natural that decision makers change their value judgment even in decision making process, because they obtain new information during the process. Therefore, decision support systems are to be robust against the change of value judgment of decision makers. To this aim, interactive p- grammingmethodswhichsearchasolutionwhileelicitingpartialinformation on value judgment of decision makers have been developed. Those methods are required to perform ?exibly for decision makers’ attitude.

Sequential Approximate Multiobjective Optimization Using Computational Intelligence

Sequential Approximate Multiobjective Optimization Using Computational Intelligence PDF Author: Hirotaka Nakayama
Publisher: Springer Science & Business Media
ISBN: 3540889108
Category : Mathematics
Languages : en
Pages : 200

Get Book Here

Book Description
Many kinds of practical problems such as engineering design, industrial m- agement and ?nancial investment have multiple objectives con?icting with eachother. Thoseproblemscanbeformulatedasmultiobjectiveoptimization. In multiobjective optimization, there does not necessarily a unique solution which minimizes (or maximizes) all objective functions. We usually face to the situation in which if we want to improve some of objectives, we have to give up other objectives. Finally, we pay much attention on how much to improve some of objectives and instead how much to give up others. This is called “trade-o?. ” Note that making trade-o? is a problem of value ju- ment of decision makers. One of main themes of multiobjective optimization is how to incorporate value judgment of decision makers into decision s- port systems. There are two major issues in value judgment (1) multiplicity of value judgment and (2) dynamics of value judgment. The multiplicity of value judgment is treated as trade-o? analysis in multiobjective optimi- tion. On the other hand, dynamics of value judgment is di?cult to treat. However, it is natural that decision makers change their value judgment even in decision making process, because they obtain new information during the process. Therefore, decision support systems are to be robust against the change of value judgment of decision makers. To this aim, interactive p- grammingmethodswhichsearchasolutionwhileelicitingpartialinformation on value judgment of decision makers have been developed. Those methods are required to perform ?exibly for decision makers’ attitude.

Computational Intelligence Applications for Software Engineering Problems

Computational Intelligence Applications for Software Engineering Problems PDF Author: Parma Nand
Publisher: CRC Press
ISBN: 100057587X
Category : Computers
Languages : en
Pages : 325

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Book Description
This new volume explores the computational intelligence techniques necessary to carry out different software engineering tasks. Software undergoes various stages before deployment, such as requirements elicitation, software designing, software project planning, software coding, and software testing and maintenance. Every stage is bundled with a number of tasks or activities to be performed. Due to the large and complex nature of software, these tasks can become costly and error prone. This volume aims to help meet these challenges by presenting new research and practical applications in intelligent techniques in the field of software engineering. Computational Intelligence Applications for Software Engineering Problems discusses techniques and presents case studies to solve engineering challenges using machine learning, deep learning, fuzzy-logic-based computation, statistical modeling, invasive weed meta-heuristic algorithms, artificial intelligence, the DevOps model, time series forecasting models, and more.

Computational Intelligence in Expensive Optimization Problems

Computational Intelligence in Expensive Optimization Problems PDF Author: Yoel Tenne
Publisher: Springer Science & Business Media
ISBN: 364210701X
Category : Technology & Engineering
Languages : en
Pages : 736

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Book Description
In modern science and engineering, laboratory experiments are replaced by high fidelity and computationally expensive simulations. Using such simulations reduces costs and shortens development times but introduces new challenges to design optimization process. Examples of such challenges include limited computational resource for simulation runs, complicated response surface of the simulation inputs-outputs, and etc. Under such difficulties, classical optimization and analysis methods may perform poorly. This motivates the application of computational intelligence methods such as evolutionary algorithms, neural networks and fuzzy logic, which often perform well in such settings. This is the first book to introduce the emerging field of computational intelligence in expensive optimization problems. Topics covered include: dedicated implementations of evolutionary algorithms, neural networks and fuzzy logic. reduction of expensive evaluations (modelling, variable-fidelity, fitness inheritance), frameworks for optimization (model management, complexity control, model selection), parallelization of algorithms (implementation issues on clusters, grids, parallel machines), incorporation of expert systems and human-system interface, single and multiobjective algorithms, data mining and statistical analysis, analysis of real-world cases (such as multidisciplinary design optimization). The edited book provides both theoretical treatments and real-world insights gained by experience, all contributed by leading researchers in the respective fields. As such, it is a comprehensive reference for researchers, practitioners, and advanced-level students interested in both the theory and practice of using computational intelligence for expensive optimization problems.

Non-Convex Multi-Objective Optimization

Non-Convex Multi-Objective Optimization PDF Author: Panos M. Pardalos
Publisher: Springer
ISBN: 3319610074
Category : Mathematics
Languages : en
Pages : 196

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Book Description
Recent results on non-convex multi-objective optimization problems and methods are presented in this book, with particular attention to expensive black-box objective functions. Multi-objective optimization methods facilitate designers, engineers, and researchers to make decisions on appropriate trade-offs between various conflicting goals. A variety of deterministic and stochastic multi-objective optimization methods are developed in this book. Beginning with basic concepts and a review of non-convex single-objective optimization problems; this book moves on to cover multi-objective branch and bound algorithms, worst-case optimal algorithms (for Lipschitz functions and bi-objective problems), statistical models based algorithms, and probabilistic branch and bound approach. Detailed descriptions of new algorithms for non-convex multi-objective optimization, their theoretical substantiation, and examples for practical applications to the cell formation problem in manufacturing engineering, the process design in chemical engineering, and business process management are included to aide researchers and graduate students in mathematics, computer science, engineering, economics, and business management.

Artificial Cognitive Architecture with Self-Learning and Self-Optimization Capabilities

Artificial Cognitive Architecture with Self-Learning and Self-Optimization Capabilities PDF Author: Gerardo Beruvides
Publisher: Springer
ISBN: 3030039498
Category : Technology & Engineering
Languages : en
Pages : 216

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Book Description
This book introduces three key issues: (i) development of a gradient-free method to enable multi-objective self-optimization; (ii) development of a reinforcement learning strategy to carry out self-learning and finally, (iii) experimental evaluation and validation in two micromachining processes (i.e., micro-milling and micro-drilling). The computational architecture (modular, network and reconfigurable for real-time monitoring and control) takes into account the analysis of different types of sensors, processing strategies and methodologies for extracting behavior patterns from representative process’ signals. The reconfiguration capability and portability of this architecture are supported by two major levels: the cognitive level (core) and the executive level (direct data exchange with the process). At the same time, the architecture includes different operating modes that interact with the process to be monitored and/or controlled. The cognitive level includes three fundamental modes such as modeling, optimization and learning, which are necessary for decision-making (in the form of control signals) and for the real-time experimental characterization of complex processes. In the specific case of the micromachining processes, a series of models based on linear regression, nonlinear regression and artificial intelligence techniques were obtained. On the other hand, the executive level has a constant interaction with the process to be monitored and/or controlled. This level receives the configuration and parameterization from the cognitive level to perform the desired monitoring and control tasks.

Introduction to the Theory of Nonlinear Optimization

Introduction to the Theory of Nonlinear Optimization PDF Author: Johannes Jahn
Publisher: Springer Nature
ISBN: 3030427609
Category : Business & Economics
Languages : en
Pages : 325

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Book Description
This book serves as an introductory text to optimization theory in normed spaces and covers all areas of nonlinear optimization. It presents fundamentals with particular emphasis on the application to problems in the calculus of variations, approximation and optimal control theory. The reader is expected to have a basic knowledge of linear functional analysis.

Multiple Criteria Decision Making

Multiple Criteria Decision Making PDF Author: M. Murat Köksalan
Publisher: World Scientific
ISBN: 9814335592
Category : Business & Economics
Languages : en
Pages : 210

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Book Description
Ch. 1. The early history of MCDM -- ch. 2. MCDM developments in the 1970s -- ch. 3. MCDM developments in the 1980s -- ch. 4. MCDM developments in the 1990s and beyond -- ch. 5. MCDM conferences -- ch. 6. MCDM society traditions -- ch. 7. Awards and presidents -- ch. 8. Biographies of leading MCDM scholars -- ch. 9. Conclusion

Multiple Criteria Decision Making: From Early History To The 21st Century

Multiple Criteria Decision Making: From Early History To The 21st Century PDF Author: Murat Koksalan
Publisher: World Scientific
ISBN: 9814462233
Category : Business & Economics
Languages : en
Pages : 210

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Book Description
Multiple Criteria Decision Making (MCDM) is all about making choices in the presence of multiple conflicting criteria. MCDM has become one of the most important and fastest growing subfields of Operations Research/Management Science. As modern MCDM started to emerge about 50 years ago, it is now a good time to take stock of developments. This book aims to present an informal, nontechnical history of MCDM, supplemented with many pictures. It covers the major developments in MCDM, from early history until now. It also covers fascinating discoveries by Nobel Laureates and other prominent scholars.The book begins with the early history of MCDM, which covers the roots of MCDM through the 1960s. It proceeds to give a decade-by-decade account of major developments in the field starting from the 1970s until now. Written in a simple and accessible manner, this book will be of interest to students, academics, and professionals in the field of decision sciences.

Introduction to Civil Engineering Systems

Introduction to Civil Engineering Systems PDF Author: Samuel Labi
Publisher: John Wiley & Sons
ISBN: 1118415302
Category : Technology & Engineering
Languages : en
Pages : 1060

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Book Description
This book presents an integrated systems approach to the evaluation, analysis, design, and maintenance of civil engineering systems. Addressing recent concerns about the world's aging civil infrastructure and its environmental impact, the author makes the case for why any civil infrastructure should be seen as part of a larger whole. He walks readers through all phases of a civil project, from feasibility assessment to construction to operations, explaining how to evaluate tasks and challenges at each phase using a holistic approach. Unique coverage of ethics, legal issues, and management is also included.

Theory and Methods of Vector Optimization (Volume One)

Theory and Methods of Vector Optimization (Volume One) PDF Author: Yu. K. Mashunin
Publisher: Cambridge Scholars Publishing
ISBN: 1527548775
Category : Mathematics
Languages : en
Pages : 195

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Book Description
This first volume presents the theory and methods of solving vector optimization problems, using initial definitions that include axioms and the optimality principle. This book proves, mathematically, that the result it presents for the solution of the vector (multi-criteria) problem is the optimal outcome, and, as such, solves the problem of vector optimization for the first time. It shows that applied methods of solving vector optimization problems can be used by researchers in modeling and simulating the development of economic systems and technical (engineering) systems.