Beschreibung
Inhaltsangabe1 Multicriteria Optimization-Fundamentals and Motivation.- 1.1 Introduction.- 1.1.1 On the Historical Development of Optimization Techniques.- 1.1.2 Necessity of Applying Optimization Techniques to the Design Process.- 1.1.3 Multicriteria Optimization as a Strategy in the Design Process.- 1.2 Mathematical Fundamentals.- 1.2.1 General Definitions and Notations in Scalar Optimization.- 1.2.2 The Multicriteria Programming Problem.- 1.2.3 The Multicriteria Control Problem.- 1.3 Components and Plants with their Objectives.- 1.3.1 Optimum Design of Highly Accurate Parabolic Antennas.- 1.3.2 Optimal Layout of a Novel Solar Energy Collector.- 1.3.3 Shape Optimization of Satellite Tanks.- 1.3.4 Optimal Shape Design.- 1.3.5 Optimal Layout of Tube-Flange Structures.- 1.4 Conclusion.- References.- I Procedures.- 2 Optimization Procedure SAPOP-A General Tool for Mu1ticriteria Structural Designs.- 2.1 Demands on an Optimization Procedure.- 2.2 Structure of the Optimization Procedure.- 2.2.1 Definitions.- 2.2.2 Three-Columns Concept.- 2.3 Basic Ideas of the Procedure SAPOP.- 2.3.1 Problem Formulation and Input Data.- 2.3.2 SAPOP Main Module.- 2.3.3 Evaluation of the Optimization Results.- 2.4 Optimization Modelling.- 2.4.1 Design Models.- 2.4.2 Evaluation Models.- 2.4.3 Sensitivity Analysis.- 2.5 Description of Two Optimization Algorithms.- 2.5.1 Sequential Linear Programming Method (SEQLI).- 2.5.2 Hybrid Method of Quadratic Programming with Reduced Line-Search Technique (QPRLT).- 2.6 Comparison with other Structural Optimization Software Systems.- 2.7 Application Example.- 2.8 Conclusion.- References.- 3 Interactive Multicriteria Optimization in Design Process.- 3.1 Introduction.- 3.2 Interactive Multicriteria Optimization Procedures.- 3.2.1 General Remarks on Classification.- 3.2.2 Approach by Fandel.- 3.2.3 STEP-Method.- 3.2.4 Approach by Jahn.- 3.2.5 Approach by Geoffrion.- 3.3 Software Package DIALOG.- 3.3.1 Basic Structure.- 3.3.2 Interactive MO-Layout of a Conical Shell.- 3.4 Software Package CAMOS.- 3.4.1 Optimization Algorithms Used in CAMOS.- 3.4.2 Multicriteria Strategy Approaches.- 3.4.3 Description of CAMOS.- 3.4.4 Interactive MO-Layouts of a Machine Tool Spindle.- 3.5 Conclusion.- References.- 4. Knowledge Engineering and Multicriteria. Optimization.- 4.1 Introduction.- 4.2 Knowledge Engineering.- 4.2.1 General Concept.- 4.2.2 Architecture of a Knowledge-Based System.- 4.3 Role of a Knowledge-Based Approach in Multicriteria Optimization.- 4.4 Knowledge-Based Optimization Formulation.- 4.4.1 Description and Representation of Optimization Problems.- 4.4.2 Mathematical Symbolic Manipulation.- 4.4.3 Mathematical Formulation of Optimization Problems.- 4.5 Knowledge-Based Optimization Control.- 4.5.1 Recognition of Optimization Formulation.- 4.5.2 Optimization Algorithm Selection.- 4.5.3 Knowledge-Based Control in Pareto-Optimal Set Generation.- 4.6 Illustration Example.- 4.6.1 System Implementation.- 4.6.2 Knowledge-Based Optimization Formulation and Recognition.- 4.6.3 Knowledge-Based Control in Pareto-Optimal Set Generation.- 4.7 Conclusion.- References.- II Applications.- 5 Mechanisms and Dynamic Systems.- 5.1 Optimal Counterweight Balancing of Robot Arms Using Multicriteria Approach.- 5.1.1 Introduction.- 5.1.2 Kinetic Model of a Robot Arm.- 5.1.3 Formulation of the Optimization Problem.- 5.1.4 Solution Method.- 5.1.5 Pareto-Optimal Designs.- 5.1.6 Conclusion.- References.- 5.2 Multicriteria Optimization of Computationally Expensive Functions and its Application to Robot Spring Balancing Mechanism Design.- 5.2.1 Introduction.- 5.2.2 General Description of the Method.- 5.2.3 Optimum Design of Spring Balancing Mechanisms of Industrial Robots.- 5.2.4 Computer Aided Optimum Design of a Robot Spring Balancing Mechanism.- 5.2.5 Conclusion.- References.- 5.3 On the Optimal Synthesis of an Automotive Drive Train.- 5.3.1 The Automotive Drive Train.- 5.3.2 The Mechanical Model.- 5.3.3 The Optimization Model.- 5.3.4 The Solution Procedure.
