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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.
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.
The proceedings volume presents selected papers from the
International Conference on Sustainability in Software Engineering
& Business Information Management: Innovation &
Applications (SSEBIM 2021) held in Olten, Switzerland from 8-9
October, 2021. 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 the recent research on hybrid intelligent
systems and their various practical applications. 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. A
premier conference in the field of artificial intelligence, HIS -
NaBIC 2020 brought together researchers, engineers and
practitioners whose work involves intelligent systems, network
security and their applications in industry. Including
contributions by authors from 25 countries, the book offers a
valuable reference guide for all researchers, students and
practitioners in the fields of science and engineering.
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. The first two chapters provide general introductions
to logistics and supply chain management on the one hand, and to
computational intelligence on the other hand. The subsequent
chapters cover specific fields in logistics and supply chain
management, work out the most relevant problems found in those
fields, and discuss approaches for solving them. Chapter 3
discusses problems in the field of production and inventory
management. Chapter 4 considers planning activities on a finer
level of granularity which is usually denoted as scheduling. In
chapter 5 problems in transportation planning such as different
types of vehicle routing problems are considered. While chapters 3
to 5 rather discuss planning problems which appear on an operative
level, chapter 6 discusses the strategic problem of designing a
supply chain or network. The final chapter provides an overview of
academic and commercial software and information systems for the
discussed applications. There appears to be a gap between general
textbooks on logistics and supply chain management and more
specialized literature dealing with methods for computational
intelligence, operations research, etc., for solving the complex
operational problems in these fields. For readers, it is often
difficult to proceed from introductory texts on logistics and
supply chain management to the sophisticated literature which deals
with the usage of advanced methods. This book fills this gap by
providing state-of-the-art descriptions of the corresponding
problems and suitable methods 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. The first two chapters provide general introductions
to logistics and supply chain management on the one hand, and to
computational intelligence on the other hand. The subsequent
chapters cover specific fields in logistics and supply chain
management, work out the most relevant problems found in those
fields, and discuss approaches for solving them. Chapter 3
discusses problems in the field of production and inventory
management. Chapter 4 considers planning activities on a finer
level of granularity which is usually denoted as scheduling. In
chapter 5 problems in transportation planning such as different
types of vehicle routing problems are considered. While chapters 3
to 5 rather discuss planning problems which appear on an operative
level, chapter 6 discusses the strategic problem of designing a
supply chain or network. The final chapter provides an overview of
academic and commercial software and information systems for the
discussed applications. There appears to be a gap between general
textbooks on logistics and supply chain management and more
specialized literature dealing with methods for computational
intelligence, operations research, etc., for solving the complex
operational problems in these fields. For readers, it is often
difficult to proceed from introductory texts on logistics and
supply chain management to the sophisticated literature which deals
with the usage of advanced methods. This book fills this gap by
providing state-of-the-art descriptions of the corresponding
problems and suitable methods for solving them.
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.
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.
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.
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.
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Advances in Signal Processing and Intelligent Recognition Systems - 6th International Symposium, SIRS 2020, Chennai, India, October 14-17, 2020, Revised Selected Papers (Paperback, 1st ed. 2021)
Sabu M. Thampi, Sri Krishnan, Rajesh M. Hegde, Domenico Ciuonzo, Thomas Hanne, …
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R1,586
Discovery Miles 15 860
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Ships in 10 - 15 working days
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This book constitutes the refereed proceedings of the 6th
International Symposium on Advances in Signal Processing and
Intelligent Recognition Systems, SIRS 2020, held in Chennai, India,
in October 2020. Due to the COVID-19 pandemic the conference was
held online. The 22 revised full papers and 5 revised short papers
presented were carefully reviewed and selected from 50 submissions.
The papers cover wide research fields including information
retrieval, human-computer interaction (HCI), information
extraction, speech recognition.
Das Buch zeigt komplexe Probleme in den Bereichen Logistik und
Supply Chain Management und eroertert fortschrittliche Methoden,
insbesondere aus dem Bereich Computational Intelligence (CI), zu
deren Loesung. Die ersten beiden Kapitel bieten allgemeine
Einfuhrungen in die Logistik, das Lieferkettenmanagement und in die
Computational Intelligence. Die folgenden Kapitel behandeln
spezifische Bereiche der Logistik und des Supply Chain Managements
und diskutieren Loesungsansatze. In Kapitel 3 werden Probleme der
Transportplanung, wie z. B. Arten von Vehicle Routing, betrachtet.
In Kapitel 4 werden Probleme aus dem Bereich der Produktions- und
Lagerverwaltung eroertert. Kapitel 5 befasst sich mit
Planungsaktivitaten beim Scheduling. Wahrend in den Kapiteln 3 bis
5 eher Planungsprobleme auf operativer Ebene behandelt werden, geht
es in Kapitel 6 um das strategische Problem der Gestaltung einer
Lieferkette oder eines Netzwerks. Das letzte Kapitel gibt einen
UEberblick uber akademische und kommerzielle Software und
Informationssysteme fur die diskutierten Anwendungen. Es scheint
eine Lucke zu geben zwischen allgemeinen Lehrbuchern uber Logistik
und Supply Chain Management und speziellerer Literatur, die sich
mit Methoden der Computational Intelligence, des Operations
Research usw. zur Loesung komplexer betrieblicher Probleme in
diesen Bereichen befasst. Fur den Leser ist es oft schwierig, von
einfuhrenden Texten uber Logistik und Supply Chain Management zu
der anspruchsvollen Literatur uber die Anwendung fortgeschrittener
Methoden uberzugehen. Dieses Buch fullt diese Lucke, indem es
Beschreibungen der entsprechenden Probleme und geeignete Methoden
zu ihrer Loesung auf dem neuesten Stand der Technik bereitstellt.
Dieses Buch ist eine UEbersetzung einer deutschen Originalausgabe.
Die UEbersetzung wurde mit Hilfe von kunstlicher Intelligenz
(maschinelle UEbersetzung durch den Dienst DeepL.com) erstellt.
Eine anschliessende menschliche UEberarbeitung erfolgte vor allem
in Bezug auf den Inhalt, so dass sich das Buch stilistisch anders
liest als eine herkoemmliche UEbersetzung.
This book highlights recent research on intelligent systems and
nature-inspired computing. It presents 132 selected papers from the
21st International Conference on Intelligent Systems Design and
Applications (ISDA 2021), which was held online. 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. Including contributions by authors from
34 countries, the book offers a valuable reference guide for all
researchers, students and practitioners in the fields of Computer
Science and Engineering.
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