Real-World Decision Support Systems Case Studies

• Main Authors: Papathanasiou, Jason, Ploskas, Nikolaos, Linden, Isabelle
• Format: eBook
• Language: English
• Published: Cham Springer Nature 2016; Springer International Publishing AG; Springer International Publishing; Springer
• Edition: 1
• Series: Integrated Series in Information Systems
• Subjects: Computer Science; Data processing Computer science; Decision making; Decision support systems; Information Systems Applications (incl. Internet); IT in Business; Management information systems; Operations Research/Decision Theory; Software Engineering
• ISBN: 9783319439167; 3319439162; 9783319439150; 3319439154
• ISSN: 1571-0270; 2197-7968
• DOI: 10.1007/978-3-319-43916-7

This book presents real-world decision support systems, i.e., systems that have been running for some time and as such have been tested in real environments and complex situations;

Table of Contents:

• 3.7.3 User Interface -- 3.7.4 Classification -- 3.8 Lessons Learned -- 3.9 Conclusions -- References -- 4 Decision Support Systems for Energy Production Optimization and Network Design in DistrictHeating Applications -- 4.1 Introduction -- 4.2 Business Issue n. 1: District Heating Network Design -- 4.2.1 Literature -- 4.2.2 System Requirements Analysis and System Design -- 4.2.3 System Development and User Interface Design -- 4.2.4 Optimization Module -- 4.2.5 System User Experience -- 4.3 Business Issue n. 2: Energy Production Management -- 4.3.1 Literature -- 4.3.2 System Requirements Analysis and System Design -- 4.3.3 System Development and User Interface Design -- 4.3.4 Optimization Module -- 4.3.5 System User Experience -- 4.4 Conclusions -- References -- 5 Birth and Evolution of a Decision Support System in the Textile Manufacturing Field -- 5.1 Introduction -- 5.1.1 The Problem -- 5.1.2 The Need for a DSS -- 5.1.3 Target Group -- 5.1.4 Existing Procedures -- 5.1.5 Classification -- 5.1.6 Underlying Technologies -- 5.2 System Requirements Analysis -- 5.2.1 Requirements Gathering -- 5.2.2 Requirement Determination and Definition -- 5.2.3 Final System Proposal -- 5.3 System Design and Development -- 5.3.1 The Problem -- Terminology -- 5.3.2 Class Diagram -- Order -- StockPiece -- Map -- FabricSheet -- UserDefinedConstraint -- 5.3.3 Activity Diagram -- 5.4 User Interface -- 5.4.1 A Typical DSS Usage -- Import from SAP -- Parameters Setting -- User-Defined Constraints -- Check and Run -- 5.4.2 Results and Graphical Maps -- Graphical Maps -- Orders vs Sheets -- KPIs -- 5.5 System Implementation -- 5.5.1 Problem Statement -- 5.5.2 Pattern Generation -- 5.5.3 ILP Model -- 5.6 System User Experience -- 5.6.1 Lessons Learnt -- 5.6.2 System Sustainability -- 5.6.3 System Upgrade and Maintenance Issues -- 5.7 Conclusions -- Appendix: Mathematical Model
• 11 SINGRAR-A Distributed Expert System for Emergency Management: Context and Design -- 11.1 Introduction -- 11.1.1 General Considerations -- 11.1.2 Problem Characterization -- 11.1.3 SINGRAR General Characteristics -- 11.2 System Requirements Analysis -- 11.2.1 Context of Use -- 11.2.2 User and Organizational Requirements -- 11.3 System Design -- 11.3.1 Knowledge Management -- 11.3.1.1 Knowledge Acquisition -- 11.3.1.2 Knowledge Coding -- 11.3.1.3 Knowledge Inferencing -- 11.3.1.4 Knowledge Transfer -- 11.3.2 Other SINGRAR Design Features -- 11.4 System Development -- 11.4.1 System Architecture -- 11.4.2 Intelligent System's Typology -- 11.4.3 Knowledge Domains -- 11.4.4 Customization -- 11.4.5 SINGAR Project Chronology -- 11.5 Conclusion -- References -- 12 SINGRAR-A Distributed Expert System for Emergency Management: Implementation and Validation -- 12.1 Introduction -- 12.2 User Interface Design -- 12.3 System Implementation -- 12.3.1 Repair Priorities Inference Model -- 12.3.2 Resource Assignment Inference Model -- 12.3.3 Forward and Backward Chaining in the Inference Process -- 12.4 System Usability -- 12.4.1 SINGRAR Usability Analysis Using SUMI Method -- 12.4.2 Dynamic Analysis of the Application -- 12.4.3 Analysis of Interfaces and User Interaction -- 12.5 Conclusions -- References -- 13 Crop Protection Online-Weeds: A Case Study for Agricultural Decision Support Systems -- 13.1 Introduction -- 13.2 System Requirements Analysis -- 13.3 System Design and Problem Solving Technic -- 13.4 User Interface Design -- 13.5 System Implementation -- 13.6 System User Experience -- 13.7 Conclusions -- References -- Index
• QDL -- ILP Model -- QDL Minimization Objective -- Stock Piece Maximum Length Usage -- Order Required Quantity -- Cut-Lengths -- Finish -- Secondary Objective -- References -- 6 A Decision Analytical Perspective on PublicProcurement Processes -- 6.1 Introduction -- 6.2 Decision Analysis for Procurement -- 6.2.1 Unreasonable Precision -- 6.2.2 Handling Value Scales Over Qualitative Estimates -- 6.2.3 Deficiencies in the Handling of Value Scales -- 6.3 System Requirement Analysis -- 6.4 System Design -- 6.4.1 Node Constraint Set -- 6.4.2 Comparing Alternatives -- 6.5 System Development -- 6.6 User Interface Design -- 6.7 System Implementation -- 6.8 System User Experience -- 6.9 Concluding Remarks -- References -- 7 Evaluation Support System for Open Challenges on Earth Observation Topics -- 7.1 Introduction -- 7.2 Evaluation Support System (ESS) Design -- 7.3 Evaluation Support System Requirements Analysis -- 7.3.1 Criteria Definition -- 7.3.2 Normalization -- 7.3.3 Criteria Relative Importance with Weighting Functions -- 7.4 User Interface Design -- 7.5 Evaluation Support System Process: Hierarchical Synthetizing Process for Rating -- 7.5.1 Bottom-Up Hierarchical Synthetizing Process (HSP) -- 7.5.2 Rating Process -- 7.5.2.1 Rating Layers 4 and 5 (Step 5) -- 7.5.2.2 Rating Layers 1, 2 and 3 (Step 6) -- 7.6 System User Experience (Experimental Cases) -- 7.6.1 Example for Demonstrating Step-by-Step Method -- 7.6.2 Illustrative Case for Demonstrating Peer Comparisonof Results -- 7.7 Conclusions -- References -- 8 An Optimization Based Decision Support System for Strategic Planning in Process Industries: The Case of a Pharmaceutical Company -- 8.1 Introduction -- 8.2 Literature Review and Motivation -- 8.2.1 Literature Review on Real-World Applications of a DSS -- 8.2.2 Motivation for the Development of the Proposed DSS
• Intro -- Foreword -- Preface -- References -- Contents -- Contributors -- List of Reviewers -- About the Editors -- 1 Computerized Decision Support Case Study Research: Concepts and Suggestions -- 1.1 Introduction -- 1.2 Understanding Decision Support Systems -- 1.3 Decision Support Case Studies -- 1.4 Examples of DSS Case Studies -- 1.5 How Useful Are DSS Case Studies -- 1.6 Conclusions and Recommendations -- Note -- References -- 2 ArgMed: A Support System for Medical Decision Making Based on the Analysis of Clinical Discussions -- 2.1 Introduction -- 2.2 An Iterative Approach to System Development: From Requirements Collection to Field Testing -- 2.3 Requirements and System Architecture -- 2.3.1 ArgMed Requirements -- 2.3.2 System Architecture -- 2.4 System Design and Implementation -- 2.4.1 Discussion Documentation -- 2.4.2 Discussion Interpretation -- 2.4.3 Discussion Analysis -- 2.4.4 ArgMed Implementation -- 2.5 User Interaction -- 2.5.1 A Clinical Discussion -- 2.5.2 Discussion Documentation -- 2.5.3 Discussion Interpretation -- 2.5.4 Discussion Analysis -- 2.6 ArgMed Experimentation -- 2.7 Conclusions -- References -- 3 The Integration of Decision Analysis Techniques in High-Throughput Clinical Analyzers -- 3.1 Introduction -- 3.2 The Technological Issues of Immunoassay Analyzers -- 3.2.1 The Biochemical Point of View -- 3.2.2 The Engineering Point of View -- 3.3 The Operational Planning in High-Throughput Clinical Analyzers -- 3.4 OR-Driven Solutions to Operational Planning -- 3.4.1 The Proposed Optimization Algorithm: SPT2 -- 3.5 Computational Results -- 3.6 Quantifiable Benefits -- 3.6.1 The Clinical Utility Gain -- 3.6.2 Clinical Benefits -- 3.6.3 Monetary Benefits -- 3.7 System Design and Development -- 3.7.1 Class Diagram -- 3.7.1.1 Batch -- 3.7.1.2 Job -- 3.7.1.3 Machine -- 3.7.1.4 Scheduler -- 3.7.2 Activity Diagram
• 8.3 Stochastic Linear Programming (SLP): An Illustrative Model -- 8.4 Decision Support System -- 8.4.1 Modeling the Pharmaceutical Industry's Production Operations -- 8.4.1.1 Fundamental Elements of Process Industry Production System -- 8.4.1.2 Model Assumptions -- 8.4.1.3 Optimization Steps -- 8.4.2 Database Structure -- 8.4.3 User Interface Development Experience -- 8.4.4 Model and DSS Validation -- 8.5 Application of the DSS to a Pharmaceutical Company -- 8.5.1 The Scale and Scope of Optimization -- 8.5.2 The Process Flow of Tablet Production -- 8.5.3 Stochastic Optimization and Scenario Experiments -- 8.5.3.1 Stochastic Optimization Model -- 8.5.3.2 Variants of the Model -- 8.5.3.3 Stochastic Experiments Design -- 8.6 Results: Analysis and Discussion -- 8.7 User Experiences -- 8.7.1 Lessons from the End User Perspective -- 8.7.2 Key Characteristics of a Good Model-Based DSS -- 8.7.3 Challenges Addressed in Model-Based DSS -- 8.8 Conclusions -- References -- 9 Decision Support in Water Resources Planning and Management: The Nile Basin Decision Support System -- 9.1 Introduction -- 9.2 Main Characteristics of the Nile Basin and the NB DSS -- 9.3 Users and System Requirements -- 9.4 System Design and Components -- 9.5 System Implementation -- 9.6 User Interface Design -- 9.7 Cases Analyzed with NB DSS -- 9.8 Experiences and Future Prospects for NB DSS -- 9.9 Conclusions -- References -- 10 The AFM-ToolBox to Support Adaptive Forest Management Under Climate Change -- 10.1 Introduction -- 10.2 System Requirements Analysis -- 10.3 System Design -- 10.3.1 ToolBox DataBase and ToolBox Client -- 10.3.2 Content Management System and Knowledge Base -- 10.3.3 Tools -- 10.4 System Development -- 10.5 User Interface Design -- 10.6 System Implementation -- 10.7 System User Experience -- 10.8 Conclusions -- References