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Student Number 93342010 Author Yu-Lin Shih(¬I¦öªL) Author's Email Address 93342010@cc.ncu.edu.tw Statistics This thesis had been viewed 526 times. Download 55 times. Department Civil Engineering Year 2009 Semester 2 Degree Ph.D. Type of Document Doctoral Dissertation Language English Title Optimal Scheduling and Solution Algorithms for the Highway Emergency Repair Problem under Large-Scale Supply-Demand Perturbations Date of Defense 2010-07-02 Page Count 110 Keyword ant colony system algorithm emergency repair large-scale supply-demand perturbation threshold accepting algorithm time-space network Abstract Natural disasters, such as earthquakes, volcanic eruption, mudflows and landslides, have significant devastating effects in terms of human injuries and property damages. The 1999 Chi-chi earthquake not only indicated the low efficiency of the government for dealing with the rescue operations but also revealed the importance of the emergency repair. In the past, the emergency repair was usually planned by decision makers according to their own experiences, lacking of systematic analyses. The resultant operation could possibly be a feasible yet inferior. Recent research has developed a model that finds the optimal work team routes for emergency road repairs to improve scheduling efficiently. However, it is difficult to optimally solve the problem within the shortest possible period of time. Therefore, we first develop a solution algorithm for this problem. Furthermore, a major disaster leads to subsequent ¡§secondary¡¨ or ¡§tertiary disasters¡¨ in practice, which delays the repair time or generates new damaged points. These large-scale perturbation problems will disrupt the original work teams¡¦ repair schedule and will affect the follow-up resource assignment. In addition to the large-scale demand-side perturbation, the large-scale supply-side perturbation also affects the original schedule. For example, new work teams could be later supported by government, military or civil agencies, for more effective emergency repair. Therefore, we develop a model and solution algorithms for the highway emergency repair problem under large-scale supply-demand perturbations.

This dissertation consists of three essays. In the first essay, an ant colony system algorithm is employed, along with the threshold accepting technique, to develop an ACS-based hybrid algorithm capable of efficiently solving an emergency roadway repair time-space network flow problem. To test how well the algorithm may be applied to actual operations, a case study is carried out using data from the Chi-Chi earthquake in Taiwan. In the second essay, we develop a model and solution algorithms for the highway emergency repair problem under large-scale supply-demand perturbations. We employ the time-space network flow technique to develop a model that can help the authority decide on the best adjustment of highway emergency repair schedule. We use the C computer language, coupled with the CPLEX mathematical programming solver, to develop a heuristic algorithm for efficiently solving this problem. To evaluate the solution algorithms, we perform a case study. The results are good, showing that the model and heuristic algorithm could be useful. In the third essay, based on the problem¡¦s characteristics, and ant colony system algorithm, we further develop three global search algorithms, coupled with the techniques of the threshold accepting algorithm and efficiently solve the problem. To evaluate the solution algorithms, we perform a case study on a scale similar to that of Chi-chi earthquake. The results are good, showing that the model and the algorithms may be useful in practice.Table of Content ºKn i

Abstractii

»xÁÂiii

Contentsiv

List of Tablesvii

List of Figuresix

Chapter 1 Introduction1

Chapter 2 Essay 1: An Ant Colony System-Based Hybrid Algorithm for an Emergency Roadway Repair Time-Space Network Flow Problem5

2.1. Introduction5

2.2. The model8

2.2.1 Emergency repair time-space network8

2.2.2 The model formulation9

2.3. Development of an Ant Colony System-Based Hybrid Algorithm (ACSB)10

2.3.1 Generation of an initial solution11

2.3.2 Generation of feasible solutions12

2.3.3 State transition rule14

2.3.4 Dynamic time-space roadway network updating rule15

2.3.5 Local search16

2.3.6 Pheromone updating rules16

2.3.7 Path-and-time tracing method17

2.3.8 TA strategy18

2.3.9 Stopping criterion18

2.4. Numerical tests18

2.4.1 Data analysis and test results19

2.4.2 ACSB parameters21

2.4.2.1 Number of ants21

2.4.2.2 State transition rule parameters21

2.4.2.3 Pheromone updating rule parameters22

2.4.2.4 TA strategy parameters23

2.4.2.5 Stopping criterion parameter SU23

2.4.3 Evaluation for different roadway network patterns25

2.5. Conclusions and Suggestions30

Chapter 3 Essay 2: Optimal Scheduling for Highway Emergency Repair Problems under Large-Scale Supply-Demand Perturbations33

3.1. Introduction33

3.2. The Time-Space network design35

3.2.1 Real practices and Modeling issues35

3.2.2 Time-space network for emergency repair under large-scale supply-demand perturbations38

3.3. The model and the algorithm44

3.3.1 The model44

3.3.2. Segmenting optimization algorithm (SOPT)50

3.4. Case study51

3.4.1 Data analysis and test results51

3.4.2 The total number of back-up work teams53

3.4.3 The number of back-up work teams at each intersection54

3.4.4 The perturbation tolerance55

3.4.5 Tolerable perturbation time55

3.5. Conclusions and discussion56

Chapter 4 Essay 3: Hybrid Global Search Algorithms for Highway Emergency Repair Problems under Large-Scale Supply-Demand Perturbations58

4.1. Introduction58

4.2. The model59

4.2.1 Time-space network for emergency repair under large-scale supply-demand perturbations60

4.2.2 The model formulation61

4.3. Development of the Ant Colony System Based Hybrid Algorithms63

4.3.1 HGS-I algorithm63

4.3.1.1 Generation of feasible solutions65

4.3.2 HGS-II algorithm67

4.3.2.1 Generation of feasible solutions68

4.3.3 HGS-III algorithm70

4.3.3.1 Generation of feasible solutions71

4.4. Case Study73

4.4.1 Data analysis and test results73

4.4.2 HGS parameters75

4.4.2.1 Number of ants76

4.4.2.2 The state transition rule parameters77

4.4.2.3 The pheromone updating rule parameters77

4.4.2.4 TA strategy parameters78

4.4.2.5 Stopping criterion parameter79

4.4.2.6 Extra parameters for HGS-III79

4.4.2.7 Combinational of the individually best parameters80

4.4.3 Scenario analysis for different supply-demand situations82

4.5. Conclusions and Suggestions85

Chapter 5 Conclusions, Suggestions and Contributions87

5.1 Conclusions87

5.2 Suggestions88

5.3 Contributions89

References90

Appendix 1: The emergency repair model by Yan and Shih (2007)93

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