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Ontology-based representation of abstract optimization models for model formulation and system generation / von Dipl.-Math. Florian Stapel. Gutachter: 1. Prof. Dr. Leena Suhl ; 2. Prof. Dr. Taïb Mellouli. Paderborn, 2016
Inhalt
Introduction
Approach within this Thesis
Outline and Methodology
Software Services and Ontologies
Component-Based Software Engineering
Services, SaaS and SOA
Web Services
The Visions of Semantic Web and OTF Computing
Ontologies
Ontology Languages and Semantics
Visualization of Ontologies within this Thesis
Reasoning, Queries and Rules
Ontology Imports and Ontology Mapping
Semantic Services
Semantic Service Description Languages
Semantic Service Composition
Data Mediation in Sequential Workflows
Model Management and Optimization Software
Basic Notions
Model Management
Modeling Lifecycle and Model Formulation
Structured Modeling
Model Integration and Composition
Distributed Model Management and SOA
Optimization Software
Solver Software
Algebraic Modeling Systems
Distributed Optimization, Frameworks and SOA
Conclusion
Problem Identification and Objectives
Problem Identification and Motivation
Requirements
Ontology-based Representation of Optimization Models
Basic Approach
A First Example Model: Min-Cost-Flow with integrality Requirements
Structure of the Representation
Ontology Structure
Top Level Definitions in OM
The Set-Parameter-Indexing Vocabulary
The Mathematical Properties Ontology
Ontology Specifications for the Min-Cost-Flow Problem
Expression Structure Separation and AML Derivation
Flow Type Example of a Statement Derivation
Requirements and Design Considerations for Queries and Derivation Implementations
A Balance-Type Example of a Statement Derivation
Algebraic Model Derivation Process
Conclusion of Statement Derivation and Structure
Reengineering of AML Models
Model Instantiation Services
Obtaining Model Properties from the Ontology Representation
Generating Model Instantiation and Solver Service Descriptions
Conclusion
Reusability and Model Formulation in the Ontology Representation
Considerations for Min-Cost-Flow Models
The Single Commodity Balance Hierarchies
Considerations for a Multicommodity Flow Model
Two Types with Generic Summations
Ontology Specifications for a general Min-Cost-Flow Model
Discussion of MDO and Formulation Ontology Type Design
Considerations for a Water Network Case Study
Introduction to Water Distribution Systems Planning
The Case Study Model
Pipe Headloss and Linearization Types
Model Formulation Considerations
Types and Formulation Choices concerning Integrality Requirements
Soft Constraints
Conclusion
Consolidation: A MINLP Model for Pipe Renewal Planning
Literature Review: Pipe Renewal Planning and Optimization
Multiperiod Renewal Planning: Problem Statement and Approach
MINLP Model
Numerical Results
Test Network
Results with Bonmin
Results with Baron
Conclusion
Tool Support
Funtionality
Design
Conclusion and Outlook
Conclusion
Outlook
Bibliography
Common Shortcuts
Ontology Definitions and Digital Material
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