Investigating Distributed Approaches for Solving Discrete, Multistage Optimization Problems

Inhaltsverzeichnis (Table of Contents)

• 1. Introduction
• 2. Optimization
  • 2.1 Introduction
  • 2.2 Simulation-Based Optimization
    • 2.2.1 Background
    • 2.2.2 Applications
  • 2.3 Parallel and Distributed Computing
    • 2.3.1 Background
    • 2.3.2 Applications
  • 2.4 Grid Computing
    • 2.4.1 Background
    • 2.4.2 Applications
    • 2.4.3 Future Prospects
  • 2.5 Performance Evaluation
    • 2.5.1 Speedup
    • 2.5.2 Efficiency
    • 2.5.3 Scalability
• 3. Discrete Multistage Processes
  • 3.1 Introduction
  • 3.2 Discrete Multistage Manufacturing Processes
  • 3.3 Challenges
• 4. Solution Approaches
  • 4.1 Introduction
  • 4.2 Simplex Approaches
  • 4.3 Evolutionary Approaches
  • 4.4 Mixed Integer Approaches
• 5. Implementation of Two Algorithms for Solving Multistage Problems
  • 5.1 Introduction
  • 5.2 Implementation Structure
  • 5.3 Scatter Search
    • 5.3.1 Basic Heuristic
    • 5.3.2 Parallelization
    • 5.3.3 Overview
    • 5.3.4 Method Description
    • 5.3.5 Performance Evaluation
  • 5.4 Branch and Bound
    • 5.4.1 Introduction
    • 5.4.2 Basic Design
    • 5.4.3 Basic Heuristic
    • 5.4.4 Parallelization
    • 5.4.5 Overview
    • 5.4.6 Method Description
    • 5.4.7 Performance Evaluation
• 6. Applications to the Approaches
  • 6.1 Introduction
  • 6.2 Test Problems
    • 6.2.1 N-Dimensional Rosenbrock Problem
    • 6.2.2 Multistage Test Problem
  • 6.3 Test Results
    • 6.3.1 Scatter Search
    • 6.3.2 Branch and Bound
    • 6.3.3 Grid Environment
• 7. Summary and Future Work

Zielsetzung und Themenschwerpunkte (Objectives and Key Themes)

This diploma thesis investigates distributed approaches for solving discrete, multistage optimization problems. The work explores theoretical backgrounds of optimization, focusing on simulation-based and distributed optimization methods. It investigates and implements solution strategies for derivative-free search methods and addresses the specific challenge of multistage optimization, where the results of each stage depend on previous stages.

• Simulation-based optimization and its challenges.
• Distributed algorithms for solving multistage problems.
• Implementation and evaluation of Scatter Search and Branch and Bound algorithms.
• Application of the algorithms to specific test problems.
• Performance evaluation of the implemented algorithms.

Zusammenfassung der Kapitel (Chapter Summaries)

Chapter 1 introduces the topic. Chapter 2 provides background on optimization, including simulation-based and distributed optimization, and performance evaluation metrics. Chapter 3 discusses discrete multistage processes and their challenges. Chapter 4 reviews existing solution approaches, such as simplex, evolutionary, and mixed-integer methods. Chapter 5 details the implementation of two distributed algorithms: Scatter Search and a stage-based Branch and Bound algorithm. Chapter 6 presents the application of these algorithms to test problems and their corresponding results.

Schlüsselwörter (Keywords)

Multistage optimization, distributed computing, simulation-based optimization, derivative-free optimization, Scatter Search, Branch and Bound, parallel algorithms, scalability, performance evaluation.