Your email was sent successfully. Check your inbox.

An error occurred while sending the email. Please try again.

Proceed reservation?

Export
  • 1
    ISBN: 9783031447426
    Language: English
    Pages: 1 Online-Ressource(XXII, 344 p. 32 illus., 16 illus. in color.)
    Edition: 1st ed. 2023.
    Series Statement: Studies in Computational Intelligence 1121
    Parallel Title: Erscheint auch als
    Parallel Title: Erscheint auch als
    Parallel Title: Erscheint auch als
    Keywords: Computational intelligence. ; Artificial intelligence. ; Operations research.
    Abstract: Foundations of Decision -- Technique for Order Preferences by Similarity to Ideal Solutions (TOPSIS) in uncertainty environment -- The Measuring Attractiveness by a Categorical Based Evaluation Technique (MACBETH) in uncertainty environment -- The Multi-Objective Optimization Ratio Analysis (MOORA) in uncertainty environment.
    Abstract: Authored by a leading expert in the field, this book introduces an innovative methodology that harnesses the power of fuzzy logic to enhance decision-making in multi-attribute scenarios. In a world of complexity and uncertainty, effective decision-making is paramount. Springer proudly presents a cutting-edge publication that revolutionizes decision analysis: "Fuzzy Decision Analysis: Multi-attribute Decision-Making Approach." This book stands at the forefront of decision analysis, introducing the integration of fuzzy logic into multi-attribute decision-making. It is a transformative journey into the realm of advanced decision analysis. It book not only equips you with the knowledge to comprehend the theoretical underpinnings but also empowers you to apply these insights in practical scenarios. This book serves as your indispensable companion. Its comprehensive coverage serves as a beacon, guiding you through the intricate maze of fuzzy logic and multi-attribute decision-making, ultimately empowering you to embrace innovation and master the art of making well-informed decisions in an ever-changing world.
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
  • 2
    ISBN: 9783031304033
    Language: English
    Pages: 1 Online-Ressource(IX, 185 p. 34 illus., 9 illus. in color.)
    Edition: 1st ed. 2023.
    Series Statement: Studies in Systems, Decision and Control 471
    Parallel Title: Erscheint auch als
    Parallel Title: Erscheint auch als
    Parallel Title: Erscheint auch als
    Keywords: Computational intelligence. ; Artificial intelligence. ; Operations research.
    Abstract: Basic concepts of voting -- Preferential voting based on data envelopment analysis -- Group preferential voting -- Applications of preferential voting in industry and society.
    Abstract: This book presents the theory and application of the models presented in this regard and establishes a meaningful relationship between data envelopment analysis and multi-attribute decision making. The issue of "choice" using the aggregation of voters' votes is one of the most important group decision-making issues that are always considered by decision makers in electoral systems. Voting is a method of group decision making in a democratic society that expresses the will of the majority. Voting is perhaps the simplest way to gather the opinions of experts, and this ease of application has made it a multi-attribute decision-making method in group decisions. Preferential voting is a type of voting that may refer to electoral systems or groups of the electoral system. In preferential voting, voters vote for multiple candidates, and how the candidates are arranged on the ballot is important. Researchers have made many efforts to provide models of voter aggregation, and one of the best results of these efforts is the aggregation of votes based on the policy of data envelopment analysis. Thus, in group decisions, the opinions of experts are obtained in a simple structure and consolidated in an interactive and logical structure, and the results can be a powerful tool for decision support. This book provides a complete set of voting models based on data envelopment analysis and expressing its various applications in industry and society. However, most decision-making methods do not use the opinions of experts or reduce the motivation of experts to participate in complex interactions and time, while voting methods do not have this shortcoming. This book is suitable for graduate students in the fields of industrial management, business management, industrial engineering, applied mathematics, and economics. It can also be a good source for researchers in decision science, decision support systems, data envelopment analysis, supply chain management, healthcare management, and others. The methods presented in this book can not only offer a comprehensive framework for solving the problems of these areas but also can inspire researchers to pursue new innovative hybrid methods.
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
  • 3
    ISBN: 9783031431814
    Language: English
    Pages: 1 Online-Ressource(XIV, 180 p. 32 illus., 29 illus. in color.)
    Edition: 1st ed. 2023.
    Series Statement: Studies in Big Data 138
    Parallel Title: Erscheint auch als
    Parallel Title: Erscheint auch als
    Parallel Title: Erscheint auch als
    Keywords: Engineering ; Computational intelligence. ; Big data.
    Abstract: Relationship between DEA models without explicit inputs and DEA-R models -- Finding efficient surfaces in DEA-R models -- Cost and revenue efficiency in DEA-R models -- A Novel Slack-Based Model for Efficiency and Super-efficiency in DEA-R -- A Multi-Criteria Ratio-Based Approach for Two-Stage Data Envelopment Analysis -- A novel network DEA-R model for evaluating hospital services supply chain performance -- A novel inverse DEA-R model for inputs/output estimation -- Evaluation of Two-Stage Networks based on Average Efficiency Using DEA and DEA-R with Fuzzy Data -- Stochastic network DEA-R models for two-stage systems.
    Abstract: The combination of DEA and ratio analysis is introduced as a suitable field for evaluating the performance of DMUs. In this regard, DEA-R is also proposed as a hybrid technique for calculating efficiency, ranking DMUs, and finding efficient faces. Therefore, the relationship between DEA and DEA-R provides a suitable field for researchers in the field of evaluating the performance of DMUs. The audience of this book is not limited to researchers in mathematics fields, but experts and students in industrial engineering and management fields also benefit from the topics of this book.
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
  • 4
    ISBN: 9783031282478
    Language: English
    Pages: 1 Online-Ressource(XIV, 442 p. 89 illus., 50 illus. in color.)
    Edition: 1st ed. 2023.
    Series Statement: Studies in Big Data 122
    Parallel Title: Erscheint auch als
    Parallel Title: Erscheint auch als
    Parallel Title: Erscheint auch als
    Keywords: Engineering—Data processing. ; Business logistics. ; Computational intelligence. ; Big data. ; Engineering
    Abstract: Supply Chain Management -- Performance Evaluation of Supply Chain Management -- Main models and approaches in supply chain evaluation -- Supplier Performance Evaluation Models -- Examining supply chain crises and disruptions -- Data Envelopment Analysis -- Supplier selection.
    Abstract: The authors of this book tried to make these experiences available to those interested, considering the experience of several years of training, research, and implementation of projects in the supply chain performance evaluation field. This book intends to identify the current performance and competitive position of that supply chain compared to other supply chains by presenting and reviewing the techniques and models for measuring the efficiency and performance of the supply chain. Determining the performance of a supply chain is a good description of the status quo (what is). Determining the performance of a supply chain is useful for describing the past and present of supply chain processes, and on the other hand, it can be used to set performance goals and initiate the improvement process. To realize this, a strategic framework or model is needed to be able to extract indicators related to the efficiency of the supply chain and design the appropriate model. .
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
  • 5
    ISBN: 9783031467356
    Language: English
    Pages: 1 Online-Ressource(VI, 442 p. 42 illus., 31 illus. in color.)
    Edition: 1st ed. 2024.
    Series Statement: Studies in Systems, Decision and Control 513
    Parallel Title: Erscheint auch als
    Parallel Title: Erscheint auch als
    Parallel Title: Erscheint auch als
    Keywords: Control engineering. ; Artificial intelligence.
    Abstract: This book chooses the topic which is due to the editors' experience in modeling projects in healthcare systems. Also, the transfer of experiences is the reason why mathematical modeling and decision making in the field of health are not given much attention. To this end, the new aspect of this book is the lack of reference needed to carry out projects in the field of health for researchers whose main expertise is not modeling. Students of health, mathematics, management, and industrial engineering fields are in the direct readership with this book. Different projects in the field of healthcare systems can use the topics presented in different chapters mentioned in this book.
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
Close ⊗
This website uses cookies and the analysis tool Matomo. More information can be found here...