Decision Making in Manufacturing Environment Using Graph Theory and Fuzzy Multiple Attribute Decision Making Methods


Book Description

Decision Making in Manufacturing Environment Using Graph Theory and Fuzzy Multiple Attribute Decision Making Methods presents the concepts and details of applications of MADM methods. A range of methods are covered including Analytic Hierarchy Process (AHP), Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), VIšekriterijumsko KOmpromisno Rangiranje (VIKOR), Data Envelopment Analysis (DEA), Preference Ranking METHod for Enrichment Evaluations (PROMETHEE), ELimination Et Choix Traduisant la Realité (ELECTRE), COmplex PRoportional ASsessment (COPRAS), Grey Relational Analysis (GRA), UTility Additive (UTA), and Ordered Weighted Averaging (OWA). The existing MADM methods are improved upon and three novel multiple attribute decision making methods for solving the decision making problems of the manufacturing environment are proposed. The concept of integrated weights is introduced in the proposed subjective and objective integrated weights (SOIW) method and the weighted Euclidean distance based approach (WEDBA) to consider both the decision maker’s subjective preferences as well as the distribution of the attributes data of the decision matrix. These methods, which use fuzzy logic to convert the qualitative attributes into the quantitative attributes, are supported by various real-world application examples. Also, computer codes for AHP, TOPSIS, DEA, PROMETHEE, ELECTRE, COPRAS, and SOIW methods are included. This comprehensive coverage makes Decision Making in Manufacturing Environment Using Graph Theory and Fuzzy Multiple Attribute Decision Making Methods a key reference for the designers, manufacturing engineers, practitioners, managers, institutes involved in both design and manufacturing related projects. It is also an ideal study resource for applied research workers, academicians, and students in mechanical and industrial engineering.







Decision-Making Models and Applications in Manufacturing Environments


Book Description

Multi-criteria decision-making (MCDM) has gained vast popularity for its ability to help make decisions in the presence of various similar and conflicting choices.This new volume applies the MCDM theory to solving problems and challenges in manufacturing environments. It discusses using MCDM computational methods to evaluate and select the most optimal solution or method for real-world, real-time manufacutring engineering issues. It details the decision-making process in relation materials selection; identification, assessment, and evaluation of risk; sustainability assessment; selection of green suppliers; and more. The chapter authors demonstrate the application of myriad MCDM techniques in decision-making, including MADM (multiple attribute decision-making), DEA (data envelopment analysis), fuzzy TOPSIS (technique for order preference by similarities to ideal solution), fuzzy-VIKOR (multicriteria optimization and compromise solution); MOORA (multi-objective optimization on the basis of ratio analysis), EWM (entropy weight method), (AHP) analytic hierarchy process, TODIM (TOmada de Decisao Interativa Multicriterio), and others. The volume illustrates these MCDM models in several industries and industrial processes, including for experimental analysis and optimization of drilling of glass fiber reinforced plastic, in the textile industries, for selection of refrigerants for domestic applications, and others.




Multiple Attribute Decision Making


Book Description

Decision makers are often faced with several conflicting alternatives. How do they evaluate trade-offs when there are more than three criteria? To help people make optimal decisions, scholars in the discipline of multiple criteria decision making (MCDM) continue to develop new methods for structuring preferences and determining the correct relative weights for criteria. A compilation of modern decision-making techniques, Multiple Attribute Decision Making: Methods and Applications focuses on the fuzzy set approach to multiple attribute decision making (MADM). Drawing on their experience, the authors bring together current methods and real-life applications of MADM techniques for decision analysis. They also propose a novel hybrid MADM model that combines DEMATEL and analytic network process (ANP) with VIKOR procedures. The first part of the book focuses on the theory of each method and includes examples that can be calculated without a computer, providing a complete understanding of the procedures. Methods include the analytic hierarchy process (AHP), ANP, simple additive weighting method, ELECTRE, PROMETHEE, the gray relational model, fuzzy integral technique, rough sets, and the structural model. Integrating theory and practice, the second part of the book illustrates how methods can be used to solve real-world MADM problems. Applications covered in the book include: AHP to select planning and design services for a construction project TOPSIS and VIKOR to evaluate the best alternative-fuel vehicles for urban areas ELECTRE to solve network design problems in urban transportation planning PROMETEE to set priorities for the development of new energy systems, from solar thermal to hydrogen energy Fuzzy integrals to evaluate enterprise intranet web sites Rough sets to make decisions in insurance marketing Helping readers understand how to apply MADM techniques to their decision making, this book is suitable for undergraduate and graduate students as well as practitioners.







Multiple Attribute Decision Making


Book Description

Multiple attribute decision making (MADM) procedures, a process for making preference decisions over the available alternatives which are characterized by multiple (usually conflicting) attributes are useful for improving decision making in a wide range of circumstances--from professional to managerial to political. Using real-world case examples, the authors introduce the reader to normative (for optimal decisions) MADM models. Beginning in chapter 2 with and introductions to the various attributes in a decision, the authors explore how MADM methods can be used for descriptive purposes to model the existing decision-making process, noncompensatory and scoring methods, accommodation of soft data, construction of a multiple decision support system, and the validity of methods. The authors also include a presentation of the advanced procedures of TOPSIS and ELECTRE. This manual offers social scientists an encapsulated view of MADM methods, their characteristics, applicability, and the methods for solving MADM problems.




Uncertain Multi-Attribute Decision Making


Book Description

This book introduces methods for uncertain multi-attribute decision making including uncertain multi-attribute group decision making and their applications to supply chain management, investment decision making, personnel assessment, redesigning products, maintenance services, military system efficiency evaluation. Multi-attribute decision making, also known as multi-objective decision making with finite alternatives, is an important component of modern decision science. The theory and methods of multi-attribute decision making have been extensively applied in engineering, economics, management and military contexts, such as venture capital project evaluation, facility location, bidding, development ranking of industrial sectors and so on. Over the last few decades, great attention has been paid to research on multi-attribute decision making in uncertain settings, due to the increasing complexity and uncertainty of supposedly objective aspects and the fuzziness of human thought. This book can be used as a reference guide for researchers and practitioners working in e.g. the fields of operations research, information science, management science and engineering. It can also be used as a textbook for postgraduate and senior undergraduate students.




Materials Selection for Sustainability in the Built Environment


Book Description

Materials Selection for Sustainability in the Built Environment: Environmental, Social and Economic Aspects presents the current state-of-the-art when it comes to the decision-making process for choosing construction materials to deliver sustainable construction projects. Aspects covered include the science of enhanced decision-making via operational research and machine learning techniques and how this can be implemented in various disciplines such as architecture, engineering and construction. To this end, the book discusses environmental, economic and social aspects in assessing construction materials and presents different tools and methods that can benefit and facilitate this process. Finally, the book reviews previous publications on construction material selection and presents essential discussions on the role professionals, researchers, contractors and governments play in making more sustainable decisions on the built environment. Presents a lifecycle management-based, systematic and integrated approach for sustainable construction materials selection Discusses the impact of materials selection, covering every aspect of sustainability (environmental, social and economic aspects) Looks at the concept of the circular economy Provides case studies on decision-making methods in combination with lifecycle sustainability assessments




Design Optimization of Renewable Energy Systems Using Advanced Optimization Algorithms


Book Description

This book describes applications of Jaya and Rao algorithms on real case studies concerning different renewable energy sources. In the last few decades, researchers have focused on renewable energy resources like solar energy, bio-energy, wave energy, ocean thermal energy, tidal energy, geothermal energy, and wind energy. This has resulted in the development of new techniques and tools that could harvest energy from renewable energy sources. Many researchers and scientists have focused on developing and optimizing the energy systems to extract and utilize renewable energy more efficiently. In this book, recently developed Jaya and Rao (Rao-1, Rao-2, and Rao-3) algorithms are introduced for single- and multi-objective optimization of selected renewable energy systems. The results of applications of the different versions of Jaya and Rao algorithms are compared with the other optimization techniques like GA, NSGA-II, PSO, MOPSO, ABC, etc., and the performance of the Jaya and Rao algorithms is highlighted compared to other optimization algorithms in the case of renewable energy systems. The book also includes the validation of different versions of the Jaya and Rao algorithms through the application to complex single- and multi-objective unconstrained benchmark functions. The algorithms and computer codes of different version of Jaya and Rao algorithms are included in the book that will be very much useful to readers in industry and academic research.




Advances in Thermal Engineering, Manufacturing, and Production Management


Book Description

This book presents the selected peer-reviewed proceedings of the International Conference on Thermal Engineering and Management Advances (ICTEMA 2020). The contents discuss latest research in the areas of thermal engineering, manufacturing engineering, and production management. Some of the topics covered include multiphase fluid flow, turbulent flows, reactive flows, atmospheric flows, combustion and propulsion, computational methods for thermo-fluid arena, micro and nanofluidics, renewable energy and environment sustainability, non-conventional energy resources, energy principles and management, machine dynamics and manufacturing, casting and forming, green manufacturing, production planning and management, quality control and management, and traditional and non-traditional manufacturing. The contents of this book will be useful for students, researchers as well as professionals working in the area of mechanical engineering and allied fields.