Thomas Hanne – författare

The work presented in this book is based on empirical study undertaken as a case study to understand the challenges faced in massively open online course (MOOC) based learning and experimentation to understand the challenges for presenting theoretical and practical courses. The book proposes a flexible online platform. This solution provides flexibility in distance learning processes including course enrollment, learning, evaluation, and outcome of degrees. The proposed system not only gives students freedom to choose their courses in accordance with their needs but also use earned credit towards online degrees of any university of their choice.

Multiple criteria decision-making research has developed rapidly and has become a main area of research for dealing with complex decision problems which require the consideration of multiple objectives or criteria. Since the 1980s, numerous multiple criterion decision methods have been developed which are able to solve such problems. However, the selection of an appropriate method to solve a particular decision problem is today's problem for a decision support researcher and decision-maker. This volume deals centrally with the problem of the numerous MCDM methods that can be applied to a decision problem. The book refers to this as a "meta decision problem", and it is this problem that the book analyzes. The author provides two strategies to help the decision-makers select and design an appropriate approach to a complex decision problem. Either of these strategies can be designed into a decision support system itself. One strategy is to use machine learning to design an MCDM method. This is accomplished by applying intelligent techniques, namely neural networks as a structure for approximating functions and evolutionary algorithms as universal learning methods.The other strategy is based on solving the meta decision problem interactively by selecting or designing a method suitable to the specific problem, for example, the constructing of a method from building blocks. This strategy leads to a concept of MCDM networks. Examples of this approach for a decision support system explain the possibilities of applying the elaborated techniques and their mutual interplay. The techniques outlined in the book can be used by researchers, students, and industry practitioners to better model and select appropriate methods for solving complex, multi-objective decision problems.

At a practical level, mathematical programming under multiple objectives has emerged as a powerful tool to assist in the process of searching for decisions which best satisfy a multitude of conflicting objectives, and there are a number of distinct methodologies for multicriteria decision-making problems that exist. These methodologies can be categorized in a variety of ways, such as form of model (e.g. linear, non-linear, stochastic), characteristics of the decision space (e.g. finite or infinite), or solution process (e.g. prior specification of preferences or interactive). Scientists from a variety of disciplines (mathematics, economics and psychology) have contributed to the development of the field of multicriteria decision making (MCDM) (or multicriteria decision analysis (MCDA), multiattribute decision making (MADM), multiobjective decision making (MODM), etc.) over the past 30 years, helping to establish MCDM as an important part of management science. MCDM has become a central component of studies in management science, economics and industrial engineering in many universities worldwide.This text aims to bring together "state-of-the-art" reviews and the end-of-millennium advances by leading experts on the fundamental theories, methodologies and applications of MCDM.

The work presented in this book is based on empirical study undertaken as a case study to understand the challenges faced in massively open online course (MOOC) based learning and experimentation to understand the challenges for presenting theoretical and practical courses. The book proposes a flexible online platform. This solution provides flexibility in distance learning processes including course enrollment, learning, evaluation, and outcome of degrees. The proposed system not only gives students freedom to choose their courses in accordance with their needs but also use earned credit towards online degrees of any university of their choice.

Multiple criteria decision-making research has developed rapidly and has become a main area of research for dealing with complex decision problems which require the consideration of multiple objectives or criteria. Over the past twenty years, numerous multiple criterion decision methods have been developed which are able to solve such problems. However, the selection of an appropriate method to solve a particular decision problem is today's problem for a decision support researcher and decision-maker. Intelligent Strategies for Meta Multiple Criteria Decision-Making deals centrally with the problem of the numerous MCDM methods that can be applied to a decision problem. The book refers to this as a `meta decision problem', and it is this problem that the book analyzes. The author provides two strategies to help the decision-makers select and design an appropriate approach to a complex decision problem. Either of these strategies can be designed into a decision support system itself. One strategy is to use machine learning to design an MCDM method. This is accomplished by applying intelligent techniques, namely neural networks as a structure for approximating functions and evolutionary algorithms as universal learning methods. The other strategy is based on solving the meta decision problem interactively by selecting or designing a method suitable to the specific problem, for example, the constructing of a method from building blocks. This strategy leads to a concept of MCDM networks. Examples of this approach for a decision support system explain the possibilities of applying the elaborated techniques and their mutual interplay. The techniques outlined in the book can be used by researchers, students, and industry practitioners to better model and select appropriate methods for solving complex, multi-objective decision problems.

At a practical level, mathematical programming under multiple objectives has emerged as a powerful tool to assist in the process of searching for decisions which best satisfy a multitude of conflicting objectives, and there are a number of distinct methodologies for multicriteria decision-making problems that exist. These methodologies can be categorized in a variety of ways, such as form of model (e.g. linear, non-linear, stochastic), characteristics of the decision space (e.g. finite or infinite), or solution process (e.g. prior specification of preferences or interactive). Scientists from a variety of disciplines (mathematics, economics and psychology) have contributed to the development of the field of Multicriteria Decision Making (MCDM) (or Multicriteria Decision Analysis (MCDA), Multiattribute Decision Making (MADM), Multiobjective Decision Making (MODM), etc.) over the past 30 years, helping to establish MCDM as an important part of management science. MCDM has become a central component of studies in management science, economics and industrial engineering in many universities worldwide. Multicriteria Decision Making: Advances in MCDM Models, Algorithms, Theory and Applications aims to bring together `state-of-the-art' reviews and the most recent advances by leading experts on the fundamental theories, methodologies and applications of MCDM. This is aimed at graduate students and researchers in mathematics, economics, management and engineering, as well as at practicing management scientists who wish to better understand the principles of this new and fast developing field.

It presents 58 selected papers from the 20th International Conference on Hybrid Intelligent Systems (HIS 2020) and 20 papers from the 12th World Congress on Nature and Biologically Inspired Computing (NaBIC 2020), which was held online, from December 14 to 16, 2020.

This book highlights recent research on intelligent systems and nature-inspired computing. The ISDA is a premier conference in the field of computational intelligence, and the latest installment brought together researchers, engineers and practitioners whose work involves intelligent systems and their applications in industry.

Das Buch zeigt komplexe Probleme in den Bereichen Logistik und Supply Chain Management und erörtert fortschrittliche Methoden, insbesondere aus dem Bereich Computational Intelligence (CI), zu deren Lösung.

This book highlights the recent research on soft computing, pattern recognition, nature-inspired computing, and their various practical applications.

The proceedings volume presents selected papers from the International Conference on Sustainability in Software Engineering & Business Information Management: Innovation & Applications (SSEBIM 2022) held in Olten, Switzerland from September 23-24, 2022. It includes research related to sustainability from both a business and technical point of view. From a business perspective, it not only addresses how to make the business operations more sustainable, but also considers factors such as human values, ethics, environment and responsibility of the businesses. From the technical perspective of software development companies, it focuses on sustainability in software engineering ranging from practices, tools, techniques and methods. The contributions reflect how software engineering teams exhibited pro-activeness in their approaches to lead to sustainable development of the software that is of highest quality and reliability.It is intended for a broad audience, including students, researchers and practitioners who work in software engineering and business information management fields.

This book highlights recent research on intelligent systems and nature-inspired computing. The ISDA is a premier conference in the field of artificial intelligence, and the latest installment brought together researchers, engineers, and practitioners whose work involves intelligent systems and their applications in industry.

It presents 46 selected papers focused on Industrial Applications from the 23rd International Conference on Intelligent Systems Design and Applications (ISDA 2023), which was held in 5 different cities namely Olten, Switzerland;

This book highlights recent research on intelligent systems and nature-inspired computing. The ISDA is a premier conference in the field of artificial intelligence, and the latest installment brought together researchers, engineers, and practitioners whose work involves intelligent systems and their applications in industry.

This book highlights recent research on intelligent systems and nature-inspired computing. The ISDA is a premier conference in the field of artificial intelligence, and the latest installment brought together researchers, engineers, and practitioners whose work involves intelligent systems and their applications in industry.

This book highlights recent research on intelligent systems and nature-inspired computing. The ISDA is a premier conference in the field of artificial intelligence, and the latest installment brought together researchers, engineers, and practitioners whose work involves intelligent systems and their applications in industry.

This book highlights recent research on intelligent systems and nature-inspired computing. The ISDA is a premier conference in the field of artificial intelligence, and the latest installment brought together researchers, engineers, and practitioners whose work involves intelligent systems and their applications in industry.

This book highlights recent research on intelligent systems and nature-inspired computing. The ISDA is a premier conference in the field of artificial intelligence, and the latest installment brought together researchers, engineers, and practitioners whose work involves intelligent systems and their applications in industry.

This book contains a selection of refereed and revised papers of Intelligent Informatics Track originally presented at the third International Symposium on Intelligent Informatics (ISI-2014), September 24-27, 2014, Delhi, India. The papers selected for this Track cover several intelligent informatics and related topics including signal processing, pattern recognition, image processing data mining and their applications.

This book deals with complex problems in the fields of logistics and supply chain management and discusses advanced methods, especially from the field of computational intelligence (CI), for solving them.

This book deals with complex problems in the fields of logistics and supply chain management and discusses advanced methods, especially from the field of computational intelligence (CI), for solving them.