Doktorarbeit / Dissertation, 2015
188 Seiten
This doctoral thesis aims to develop new techniques and algorithms for solving multiobjective and lexicographic goal-based shortest path problems. The research focuses on improving the efficiency and effectiveness of existing methods, exploring novel approaches, and conducting comprehensive experimental evaluations.
Chapter 1: Introduction: This chapter introduces the problem of finding shortest paths in networks with multiple objectives or lexicographic preferences. It establishes the context and motivation for the research, highlighting the importance of efficient and effective algorithms for solving these complex problems. The chapter provides a roadmap for the thesis, outlining the structure and contributions of each subsequent chapter. It sets the stage by underscoring the practical applications of efficient shortest path algorithms across various domains, from transportation networks to resource allocation problems. The limitations of existing approaches are also presented, justifying the need for innovative solutions explored in this thesis. Chapter 2: Background: This chapter provides a comprehensive review of the literature related to shortest path problems, focusing on both single-objective and multiobjective cases. It presents various established algorithms, discussing their strengths, weaknesses, and computational complexities. The chapter establishes a solid foundation for the thesis by reviewing relevant concepts in graph theory, optimization, and multi-criteria decision making. It examines different approaches to handle multiple objectives and lexicographic preferences, laying the groundwork for the novel techniques introduced in subsequent chapters. A thorough understanding of existing methods is crucial for evaluating the contributions and innovations presented in the thesis. Chapter 3: New Algorithms for Multiobjective Shortest Path Problems: This chapter presents the core contributions of the thesis regarding multiobjective shortest path problems. It details the development of new algorithms designed to enhance the efficiency and scalability of solving these problems. The chapter likely includes descriptions of the algorithms' design principles, computational complexity analysis, and implementation details. It also focuses on the innovative aspects of the proposed algorithms, highlighting the advantages compared to existing methods. Detailed comparisons and analyses of algorithmic performance are expected, perhaps including pseudo-code or flowcharts. This chapter is central to the thesis's originality and contribution to the field. Chapter 4: Lexicographic Goal-Based Shortest Path Problems: This chapter extends the work from Chapter 3 to address the more complex case of lexicographic goal-based shortest path problems. It likely presents specialized algorithms tailored to efficiently handle preferences expressed as lexicographic orderings of objectives. The chapter might discuss specific challenges involved in solving lexicographic problems and propose innovative solutions to address them. A key element is the comparison of these algorithms with those presented in Chapter 3, highlighting both similarities and differences in their performance and applicability. The chapter solidifies the thesis's contribution by demonstrating its ability to handle even more sophisticated variations of shortest path problems. Chapter 5: Experimental Results: This chapter presents the results of a thorough experimental evaluation of the algorithms developed in the previous chapters. It likely involves a description of the experimental setup, datasets used, and performance metrics employed. The results are analyzed and compared to establish the efficiency and effectiveness of the new algorithms relative to state-of-the-art techniques. Detailed tables, graphs, and statistical analysis might support the conclusions. The chapter is crucial in validating the claims about the practical applicability and performance benefits of the proposed algorithms.
Multiobjective shortest path problems, lexicographic shortest path problems, goal-based shortest paths, algorithms, graph theory, optimization, computational complexity, performance evaluation.
The document is a language preview for a doctoral thesis focusing on multiobjective and lexicographic goal-based shortest path problems.
The table of contents lists the following chapters: Introduction, Background, New Algorithms for Multiobjective Shortest Path Problems, Lexicographic Goal-Based Shortest Path Problems, and Experimental Results.
The objectives include developing new algorithms for multiobjective shortest path problems, investigating lexicographic goal-based shortest path problems, and evaluating the performance of different algorithms.
Chapter 1 introduces the problem of finding shortest paths with multiple objectives or lexicographic preferences and provides context and motivation for the research.
Chapter 2 provides a comprehensive review of existing literature on shortest path problems, including both single-objective and multiobjective cases, covering established algorithms, their strengths, weaknesses, and computational complexities.
Chapter 3 presents new algorithms developed to enhance the efficiency and scalability of solving multiobjective shortest path problems.
Chapter 4 extends the work from Chapter 3 to address lexicographic goal-based shortest path problems, presenting specialized algorithms for handling preferences expressed as lexicographic orderings of objectives.
Chapter 5 presents the results of a thorough experimental evaluation of the algorithms developed, comparing them to state-of-the-art techniques to validate their performance and applicability.
The keywords include: Multiobjective shortest path problems, lexicographic shortest path problems, goal-based shortest paths, algorithms, graph theory, optimization, computational complexity, and performance evaluation.
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