Probability-Based Multi-objective Optimization for Material Selection

Probability-Based Multi-objective Optimization for Material Selection

Author: Maosheng Zheng

Publisher: Springer

ISBN: 9811933502

Category: Technology & Engineering

Page: 0

View: 535

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This book illuminates the fundamental principle and applications of probability-based multi-objective optimization for material selection systematically, in which a brand new concept of preferable probability and its assessment as well as other treatments are introduced by authors for the first time. Hybrids of the new approach with experimental design methodologies, such as response surface methodology, orthogonal experimental design, and uniform experimental design, are all performed; the conditions of the material performance utility with desirable value and robust assessment are included; the discretization treatment of complicated integral in the evaluation is presented. The authors wish this work will cast a brick to attract jade and would make its contributions to relevant fields as a paving stone. This book can be used as a textbook for postgraduate and advanced undergraduate students in material relevant majors, and a reference book for scientists and engineers digging in the related fields.

Probability-Based Multi-objective Optimization for Material Selection

Probability-Based Multi-objective Optimization for Material Selection

Author: Maosheng Zheng

Publisher: Springer Nature

ISBN: 9789811933516

Category: Technology & Engineering

Page: 157

View: 972

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This book illuminates the fundamental principle and applications of probability-based multi-objective optimization for material selection systematically, in which a brand new concept of preferable probability and its assessment as well as other treatments are introduced by authors for the first time. Hybrids of the new approach with experimental design methodologies, such as response surface methodology, orthogonal experimental design, and uniform experimental design, are all performed; the conditions of the material performance utility with desirable value and robust assessment are included; the discretization treatment of complicated integral in the evaluation is presented. The authors wish this work will cast a brick to attract jade and would make its contributions to relevant fields as a paving stone. This book can be used as a textbook for postgraduate and advanced undergraduate students in material relevant majors, and a reference book for scientists and engineers digging in the related fields.

EVOLVE - A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation VI

EVOLVE - A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation VI

Author: Alexandru-Adrian Tantar

Publisher: Springer

ISBN: 9783319697109

Category: Technology & Engineering

Page: 226

View: 654

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This book comprises selected research papers from the 2015 edition of the EVOLVE conference, which was held on June 18–June 24, 2015 in Iași, Romania. It presents the latest research on Probability, Set Oriented Numerics, and Evolutionary Computation. The aim of the EVOLVE conference was to provide a bridge between probability, set oriented numerics and evolutionary computation and to bring together experts from these disciplines. The broad focus of the EVOLVE conference made it possible to discuss the connection between these related fields of study computational science. The selected papers published in the proceedings book were peer reviewed by an international committee of reviewers (at least three reviews per paper) and were revised and enhanced by the authors after the conference. The contributions are categorized into five major parts, which are: Multicriteria and Set-Oriented Optimization; Evolution in ICT Security; Computational Game Theory; Theory on Evolutionary Computation; Applications of Evolutionary Algorithms. The 2015 edition shows a major progress in the aim to bring disciplines together and the research on a number of topics that have been discussed in previous editions of the conference matured over time and methods have found their ways in applications. In this sense the book can be considered an important milestone in bridging and thereby advancing state-of-the-art computational methods.

Recent Advances in Technology Research and Education

Recent Advances in Technology Research and Education

Author: Dumitru Luca

Publisher: Springer

ISBN: 9783319674599

Category: Technology & Engineering

Page: 352

View: 966

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This book presents selected contributions to the 16th International Conference on Global Research and Education Inter-Academia 2017 hosted by Alexandru Ioan Cuza University of Iași, Romania from 25 to 28 September 2017. It is the third volume in the series, following the editions from 2015 and 2016. Fundamental and applied research in natural sciences have led to crucial developments in the ongoing 4th global industrial revolution, in the course of which information technology has become deeply embedded in industrial management, research and innovation – and just as deeply in education and everyday life. Materials science and nanotechnology, plasma and solid state physics, photonics, electrical and electronic engineering, robotics and metrology, signal processing, e-learning, intelligent and soft computing have long since been central research priorities for the Inter-Academia Community (I-AC) – a body comprising 14 universities and research institutes from Japan and Central/East-European countries that agreed, in 2002, to coordinate their research and education programs so as to better address today’s challenges. The book is intended for use in academic, government, and industrial R&D departments as a reference tool in research and technology education. The 42 peer-reviewed papers were written by more than 119 leading scientists from 14 countries, most of them affiliated to the I-AC.

Reliability-Based Optimization für Multiple Constraints with Evolutionary Algorithms

Reliability-Based Optimization für Multiple Constraints with Evolutionary Algorithms

Author: David Daum

Publisher: diplom.de

ISBN: 9783836618281

Category: Technology & Engineering

Page: 101

View: 972

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Inhaltsangabe:Introduction: In handling real-world optimization problems, it is often the case that the underlying decision variables and parameters cannot be controlled exactly as specified. For example, if a deterministic consideration of an optimization problem results in an optimal dimension of a cylindrical member to have a 50 mm diameter, there exists no manufacturing process which will guarantee the production of a cylinder having exactly a 50 mm diameter. Every manufacturing process has a finite machine precision and the dimensions are expected to vary around the specified value. Similarly, the strength of a material often does not remain fixed for the entire length of the material and is expected to vary from point to point. When such variations in decision variables and parameters are expected in practice, an obvious question arises: How reliable is the optimized design against failure when the suggested parameters cannot be adhered to? This question is important because in most optimization problems the deterministic optimum lies at the intersection of a number of constraint boundaries. Thus, if no uncertainties in parameters and variables are expected, the optimized solution is the best choice, but if uncertainties are expected, in most occasions, the optimized solution will be found to be infeasible, violating one or more constraints. These uncertainties, which are either controllable (e.g.imensions) or uncontrollable (e.g. material properties), are present and need to be accounted for in the design process. Assuming that the variables follow a probability distribution in practice, reliability-based design optimization (RBDO) methods find a reliable solution which is feasible with a pre-specified probability. In most RBDO problems, failure probability and costs are violating objectives, which means that when one is lowered, the other may rise. Therefore, it is important to identify the uncertain variables which have an impact on the problem and describe them with different probability distributions based on statistical calculations. Then, the ordinary deterministic constraint is replaced by a stochastic constraint which is only restricting the probability of failure for a solution, not the failure itself. This can be done for each constraint or for the complete set of constraints, for the complete structure. Different methods for evaluating the reliability of a solution exist. If the cumulative density function (CDF) with its [...]

Data-Based Methods for Materials Design and Discovery

Data-Based Methods for Materials Design and Discovery

Author: Ghanshyam Pilania

Publisher: Springer Nature

ISBN: 9783031023835

Category: Science

Page: 172

View: 364

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Machine learning methods are changing the way we design and discover new materials. This book provides an overview of approaches successfully used in addressing materials problems (alloys, ferroelectrics, dielectrics) with a focus on probabilistic methods, such as Gaussian processes, to accurately estimate density functions. The authors, who have extensive experience in this interdisciplinary field, discuss generalizations where more than one competing material property is involved or data with differing degrees of precision/costs or fidelity/expense needs to be considered.

Application of Evolutionary Algorithms for Multi-objective Optimization in VLSI and Embedded Systems

Application of Evolutionary Algorithms for Multi-objective Optimization in VLSI and Embedded Systems

Author: M.C. Bhuvaneswari

Publisher: Springer

ISBN: 9788132219583

Category: Technology & Engineering

Page: 174

View: 815

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This book describes how evolutionary algorithms (EA), including genetic algorithms (GA) and particle swarm optimization (PSO) can be utilized for solving multi-objective optimization problems in the area of embedded and VLSI system design. Many complex engineering optimization problems can be modelled as multi-objective formulations. This book provides an introduction to multi-objective optimization using meta-heuristic algorithms, GA and PSO and how they can be applied to problems like hardware/software partitioning in embedded systems, circuit partitioning in VLSI, design of operational amplifiers in analog VLSI, design space exploration in high-level synthesis, delay fault testing in VLSI testing and scheduling in heterogeneous distributed systems. It is shown how, in each case, the various aspects of the EA, namely its representation and operators like crossover, mutation, etc, can be separately formulated to solve these problems. This book is intended for design engineers and researchers in the field of VLSI and embedded system design. The book introduces the multi-objective GA and PSO in a simple and easily understandable way that will appeal to introductory readers.

Smart Structures and Materials

Smart Structures and Materials

Author: Aurelio L. Araujo

Publisher: Springer

ISBN: 9783319445076

Category: Science

Page: 293

View: 636

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This work was compiled with expanded and reviewed contributions from the 7th ECCOMAS Thematic Conference on Smart Structures and Materials, that was held from 3 to 6 June 2015 at Ponta Delgada, Azores, Portugal. The Conference provided a comprehensive forum for discussing the current state of the art in the field as well as generating inspiration for future ideas specifically on a multidisciplinary level. The scope of the Conference included topics related to the following areas: Fundamentals of smart materials and structures; Modeling/formulation and characterization of smart actuators, sensors and smart material systems; Trends and developments in diverse areas such as material science including composite materials, intelligent hydrogels, interfacial phenomena, phase boundaries and boundary layers of phase boundaries, control, micro- and nano-systems, electronics, etc. to be considered for smart systems; Comparative evaluation of different smart actuators and sensors; Analysis of structural concepts and designs in terms of their adaptability to smart technologies; Design and development of smart structures and systems; Biomimetic phenomena and their inspiration in engineering; Fabrication and testing of smart structures and systems; Applications of smart materials, structures and related technology; Smart robots; Morphing wings and smart aircrafts; Artificial muscles and biomedical applications; Smart structures in mechatronics; and Energy harvesting.

Multi-criteria Decision Analysis for Supporting the Selection of Engineering Materials in Product Design

Multi-criteria Decision Analysis for Supporting the Selection of Engineering Materials in Product Design

Author: Ali Jahan

Publisher: Butterworth-Heinemann

ISBN: 9780081005415

Category: Technology & Engineering

Page: 252

View: 816

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Multi-criteria Decision Analysis for Supporting the Selection of Engineering Materials in Product Design, Second Edition, provides readers with tactics they can use to optimally select materials to satisfy complex design problems when they are faced with the vast range of materials available. Current approaches to materials selection range from the use of intuition and experience, to more formalized computer-based methods, such as electronic databases with search engines to facilitate the materials selection process. Recently, multi-criteria decision-making (MCDM) methods have been applied to materials selection, demonstrating significant capability for tackling complex design problems. This book describes the rapidly growing field of MCDM and its application to materials selection. It aids readers in producing successful designs by improving the decision-making process. This new edition updates and expands previous key topics, including new chapters on materials selection in the context of design problem-solving and multiple objective decision-making, also presenting a significant amount of additional case studies that will aid in the learning process. Describes the advantages of Quality Function Deployment (QFD) in the materials selection process through different case studies Presents a methodology for multi-objective material design optimization that employs Design of Experiments coupled with Finite Element Analysis Supplements existing quantitative methods of materials selection by allowing simultaneous consideration of design attributes, component configurations, and types of material Provides a case study for simultaneous materials selection and geometrical optimization processes

Supply Chain Disruption Management

Supply Chain Disruption Management

Author: Tadeusz Sawik

Publisher: Springer Nature

ISBN: 9783030448141

Category: Business & Economics

Page: 467

View: 644

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This book deals with stochastic combinatorial optimization problems in supply chain disruption management, with a particular focus on management of disrupted flows in customer-driven supply chains. The problems are modeled using a scenario based stochastic mixed integer programming to address riskneutral, risk-averse and mean-risk decision-making in the presence of supply chain disruption risks. The book focuses on integrated disruption mitigation and recovery decision-making and innovative, computationally efficient multi-portfolio approach to supply chain disruption management, e.g., selection of primary and recovery supply portfolios, demand portfolios, capacity portfolios, etc. Numerous computational examples throughout the book, modeled in part on realworld supply chain disruption management problems, illustrate the material presented and provide managerial insights. Many propositions formulated in the book lead to a deep understanding of the properties of developed stochastic mixed integer programs and optimal solutions. In the computational examples, the proposed mathematical programming models are solved using an advanced algebraic modeling language such as AMPL and CPLEX, GUROBI and XPRESS solvers. The knowledge and tools provided in the book allow the reader to model and solve supply chain disruption management problems using commercially available software for mixed integer programming. Using the end-of chapter problems and exercises, the monograph can also be used as a textbook for an advanced course in supply chain risk management. After an introductory chapter, the book is then divided into six main parts. Part I addresses selection of a supply portfolio; Part II considers integrated selection of supply portfolio and scheduling; Part III looks at integrated, equitably efficient selection of supply portfolio and scheduling; Part IV examines integrated selection of primary and recovery supply and demand portfolios and production and inventory scheduling, Part V deals with selection of resilient supply portfolio in multitier supply chain networks; and Part VI addresses selection of cybersecurity safequards portfolio for disruption management of information flows in supply chains.

Materials Selection for Natural Fiber Composites

Materials Selection for Natural Fiber Composites

Author: Faris M Al,Oqla

Publisher: Woodhead Publishing

ISBN: 9780081022771

Category: Technology & Engineering

Page: 286

View: 807

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Materials Selection for Natural Fiber Composites covers the use of various tools and techniques that can be applied for natural fiber composite selection to expand the sustainable design possibilities and support cleaner production requirements. These techniques include the analytical hierarchy process, knowledge-based system, Java based materials selection system, artificial neural network, Pugh selection method, and the digital logic technique. Information on related topics, such as materials selection and design, natural fiber composites, and materials selection for composites are discussed to provide background information to the main topic. Current developments in selecting the natural fiber composite material system, including the natural fiber composites and their constituents (fibers and polymers) is the main core of the book, with in detailed sections on various technical, environmental and economic issues to enhance both environmental indices and the industrial sustainability theme. Recent developments on the analytical hierarchy process in natural fiber composite materials selection, materials selection for natural fiber composites, and knowledge based system for natural fiber composite materials selection are also discussed. Focuses on materials selection for natural fiber composites Covers potential tools and techniques, such as analytical hierarchy process, knowledge-based systems, Java-based materials selection system, artificial neural network, the Pugh selection method and digital logic technique Contains contributions from leading experts in the field

Computational Approaches to Materials Design: Theoretical and Practical Aspects

Computational Approaches to Materials Design: Theoretical and Practical Aspects

Author: Datta, Shubhabrata

Publisher: IGI Global

ISBN: 9781522502913

Category: Technology & Engineering

Page: 475

View: 380

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The development of new and superior materials is beneficial within industrial settings, as well as a topic of academic interest. By using computational modeling techniques, the probable application and performance of these materials can be easily evaluated. Computational Approaches to Materials Design: Theoretical and Practical Aspects brings together empirical research, theoretical concepts, and the various approaches in the design and discovery of new materials. Highlighting optimization tools and soft computing methods, this publication is a comprehensive collection for researchers, both in academia and in industrial settings, and practitioners who are interested in the application of computational techniques in the field of materials engineering.