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Job Shop Scheduling with Consideration of Due Dates : Potentials of Local Search Based Solution Techniques.

By: Kuhpfahl, Jens.
Material type: TextTextSeries: eBooks on Demand.Produktion und Logistik Ser: Publisher: Wiesbaden : Gabler, 2015Copyright date: ©2016Description: 1 online resource (206 pages).Content type: text Media type: computer Carrier type: online resourceISBN: 9783658102920.Subject(s): Management scienceGenre/Form: Electronic books.Additional physical formats: Print version:: Job Shop Scheduling with Consideration of Due Dates : Potentials of Local Search Based Solution TechniquesDDC classification: 658.40301 Online resources: Click here to view this ebook.
Contents:
Foreword -- Acknowlegdement -- Contents -- List of Figures -- List of Tables -- List of Notations -- List of Abbreviations -- Chapter 1 Introduction -- 1.1 Aims and Contributions of the Thesis -- 1.2 Overview of the Thesis -- 1.3 Publications -- Chapter 2 Job Shop Scheduling - Formulation and Modeling -- 2.1 Problem Structure -- 2.2 Classification into the Scheduling Theory -- 2.3 Mathematical Model and Complexity -- 2.4 The Disjunctive Graph Model -- 2.5 The Concept of the Critical Tree -- 2.6 Exemplification on the instance ft06 (f = 1.3) -- Chapter 3 Literature Review -- 3.1 Exact Algorithms -- 3.2 Dispatching Rules -- 3.3 Shifting Bottleneck Heuristic -- 3.4 Local Search based Algorithms and Techniques -- 3.5 Other Heuristic Approaches -- 3.6 Hybrid Approaches -- 3.7 Summary -- Chapter 4 Neighborhood Definitions for the JSPTWT -- 4.1 The Basic Concept of Neighborhood Search -- 4.2 Existing Neighborhoods -- 4.3 New Neighborhoods -- 4.4 Characteristics of the proposed Neighborhoods -- 4.4.1 Feasibility Property -- 4.4.2 Connectivity Property -- 4.4.3 Estimate of the Size of the Neighborhoods -- 4.5 Performance Analysis -- 4.5.1 Test Suite -- 4.5.2 Local Search with a Single Neighborhood Operator -- 4.5.3 Local Search with Pairs of Neighborhood Operators -- 4.5.4 Local Search with all Neighborhood Operators -- 4.6 Summary -- Chapter 5 Neighbor Evaluation Procedures in Local Search based Algorithms for solving the JSPTWT -- 5.1 Basic Principles -- 5.2 A Lower Bound Procedure for the Applica-tion of the CET Neighborhood -- 5.3 A Lower Bound Procedure for the Applica-tion of the SCEI Neighborhood -- 5.4 A new approach: Heads Updating -- 5.5 Performance Test -- 5.6 Summary -- Chapter 6 Solving the JSPTWT - a new Solution Procedure -- 6.1 Metaheuristic Concepts -- 6.1.1 Basic Concept of Metaheuristics -- 6.1.2 Some Metaheuristics.
6.1.3 The Fitness Landscape: a brief Side Trip -- 6.2 Algorithmic Concept for a new Solution Pro-cedure -- 6.2.1 Motivation and Overview of the Algorithmic Concept -- 6.2.2 Construction Algorithm -- 6.2.3 Improvement Algorithm -- 6.2.4 Adaptive Components -- 6.2.5 Configuration and Parameter Values -- Chapter 7 Computational Study -- 7.1 Benchmark Instances of the JSPTWT -- 7.1.1 Modification of JSP Instances -- 7.1.2 Standard Benchmark Set of Singer and Pinedo -- 7.1.3 Lawrence's Instances -- 7.2 Other Objective Functions -- 7.2.1 JSP with minimizing the Total Flow Time -- 7.2.2 JSP with minimizing the Number of Tardy Jobs -- 7.3 Summary -- Chapter 8 Conclusion -- Bibliography -- Appendix A Applying Neighborhood Operators: the example ft06 (f = 1.3) -- Appendix B Overview of considered Dispatching Rules -- Appendix C Computational Results from the Literature -- Appendix D Analysis of the EGRASP result for the problem instance orb08 (f = 1.6) -- Appendix E Computational Results for the JSPTWU.
Summary: Jens Kuhpfahl analyzes the job shop scheduling problem with minimizing the total weighted tardiness as objective. First, he provides a suitable graph representation based on a disjunctive graph formulation. Second, several key components of local search procedures are analyzed and enhanced. The resulting outputs of these investigations contribute to the development of a new solution procedure whose performance quality leads to superior computational results.
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Foreword -- Acknowlegdement -- Contents -- List of Figures -- List of Tables -- List of Notations -- List of Abbreviations -- Chapter 1 Introduction -- 1.1 Aims and Contributions of the Thesis -- 1.2 Overview of the Thesis -- 1.3 Publications -- Chapter 2 Job Shop Scheduling - Formulation and Modeling -- 2.1 Problem Structure -- 2.2 Classification into the Scheduling Theory -- 2.3 Mathematical Model and Complexity -- 2.4 The Disjunctive Graph Model -- 2.5 The Concept of the Critical Tree -- 2.6 Exemplification on the instance ft06 (f = 1.3) -- Chapter 3 Literature Review -- 3.1 Exact Algorithms -- 3.2 Dispatching Rules -- 3.3 Shifting Bottleneck Heuristic -- 3.4 Local Search based Algorithms and Techniques -- 3.5 Other Heuristic Approaches -- 3.6 Hybrid Approaches -- 3.7 Summary -- Chapter 4 Neighborhood Definitions for the JSPTWT -- 4.1 The Basic Concept of Neighborhood Search -- 4.2 Existing Neighborhoods -- 4.3 New Neighborhoods -- 4.4 Characteristics of the proposed Neighborhoods -- 4.4.1 Feasibility Property -- 4.4.2 Connectivity Property -- 4.4.3 Estimate of the Size of the Neighborhoods -- 4.5 Performance Analysis -- 4.5.1 Test Suite -- 4.5.2 Local Search with a Single Neighborhood Operator -- 4.5.3 Local Search with Pairs of Neighborhood Operators -- 4.5.4 Local Search with all Neighborhood Operators -- 4.6 Summary -- Chapter 5 Neighbor Evaluation Procedures in Local Search based Algorithms for solving the JSPTWT -- 5.1 Basic Principles -- 5.2 A Lower Bound Procedure for the Applica-tion of the CET Neighborhood -- 5.3 A Lower Bound Procedure for the Applica-tion of the SCEI Neighborhood -- 5.4 A new approach: Heads Updating -- 5.5 Performance Test -- 5.6 Summary -- Chapter 6 Solving the JSPTWT - a new Solution Procedure -- 6.1 Metaheuristic Concepts -- 6.1.1 Basic Concept of Metaheuristics -- 6.1.2 Some Metaheuristics.

6.1.3 The Fitness Landscape: a brief Side Trip -- 6.2 Algorithmic Concept for a new Solution Pro-cedure -- 6.2.1 Motivation and Overview of the Algorithmic Concept -- 6.2.2 Construction Algorithm -- 6.2.3 Improvement Algorithm -- 6.2.4 Adaptive Components -- 6.2.5 Configuration and Parameter Values -- Chapter 7 Computational Study -- 7.1 Benchmark Instances of the JSPTWT -- 7.1.1 Modification of JSP Instances -- 7.1.2 Standard Benchmark Set of Singer and Pinedo -- 7.1.3 Lawrence's Instances -- 7.2 Other Objective Functions -- 7.2.1 JSP with minimizing the Total Flow Time -- 7.2.2 JSP with minimizing the Number of Tardy Jobs -- 7.3 Summary -- Chapter 8 Conclusion -- Bibliography -- Appendix A Applying Neighborhood Operators: the example ft06 (f = 1.3) -- Appendix B Overview of considered Dispatching Rules -- Appendix C Computational Results from the Literature -- Appendix D Analysis of the EGRASP result for the problem instance orb08 (f = 1.6) -- Appendix E Computational Results for the JSPTWU.

Jens Kuhpfahl analyzes the job shop scheduling problem with minimizing the total weighted tardiness as objective. First, he provides a suitable graph representation based on a disjunctive graph formulation. Second, several key components of local search procedures are analyzed and enhanced. The resulting outputs of these investigations contribute to the development of a new solution procedure whose performance quality leads to superior computational results.

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Author notes provided by Syndetics

<p>Dr. Jens Kuhpfahl wrote his dissertation under the supervision of Prof. Dr. Christian Bierwirth at the Chair of Production and Logistics at the University of Halle (Saale).</p>

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