簡易檢索 / 詳目顯示

回結果列表
研究生： Zahra Alya Darojati
Zahra Alya Darojati
論文名稱： Multi-objective Optimization for Decision-making in Pavement Maintenance and Rehabilitation
Multi-objective Optimization for Decision-making in Pavement Maintenance and Rehabilitation
指導教授： 楊亦東
I-Tung Yang
口試委員: 廖敏志
Min-Chih Liao
余文德
Wen-Der Yu
學位類別： 碩士
Master
系所名稱： 工程學院 - 營建工程系
Department of Civil and Construction Engineering
論文出版年： 2023
畢業學年度： 111
語文別： 英文
論文頁數： 217
外文關鍵詞： Maintenance and Rehabilitation (M&R), Non-dominated Sorting Algorithm-II (NSGA-II), Multi-objective Optimization of Particle Swarm Optimization (MOPSO)
相關次數： 點閱：224  下載：2 
分享至:
查詢本校圖書館目錄 查詢臺灣博碩士論文知識加值系統 勘誤回報
  •  上一筆

    • Pavement Management Systems (PMS) cover the maintenance activity on a scheduled basis to manage the local finances and improve the pavement conditions during its service life. Thus, developing a pavement deterioration model encompassing a comprehensive database is crucial to represent reliable and effective predictions. This study collected the pavement distress information from Long-Term Pavement Performance (LTPP) to be calculated in Micro-PAVER as the basic data for determining the sigmoid parameter of the pavement performance master curve using a Pavement Condition Index (PCI). A proposed framework, Multi-objective Maintenance Strategy (MOMS), integrates the master curve with the optimization process in determining strategic Maintenance and Rehabilitation (M&R) plan for the 1043 pavement section in Taiwan using a Non-dominated Sorting Algorithm-II (NSGA-II) and Multi-Objective of Particle Swarm Optimization (MOPSO) algorithms by maximizing the average condition and minimizing the overall costs. MOMS predicts optimal M&R strategies, budget, and performance impact for five years. The result provides Pareto fronts with 17 non-dominated solutions for NSGA-II and 14 for MOPSO. The comparison shows that NSGA-II performed better by executing the least cost and greater hypervolume. Several case studies are formulated to provide valuable insights and support decision-making processes using the NSGA-II outcomes. The proposed framework will give informative tools to establish expectations and guide appropriate M&R strategy.

    ABSTRACT i ACKNOWLEDGEMENT ii TABLE OF CONTENTS viii LIST OF FIGURES viii LIST OF TABLES xi LIST OF ABBREVIATIONS xiii CHAPTER I INTRODUCTION 1 1.1. Research Background 1 1.2. Research Objective 3 1.3. Research Outline 4 1.4. Research Process and Structure 4 CHAPTER II LITERATURE REVIEW 6 2.1. Introduction 6 2.2. Pavement Management System (PMS) 6 2.2.1. Flexible Pavement Distress Type 9 2.2.2. Pavement Condition Index (PCI) 17 2.2.3. PCI Calculation Technique 20 2.2.4. Flexible Pavement Maintenance 25 2.3. Pavement Performance Deterministic Models 32 2.3.1. Mechanistic-Empirical Prediction Models 32 2.3.2. Pavement Performance Model 34 2.3.3. Data Shifting Concept 35 2.4. Optimization in Pavement Maintenance Scheduling 37 2.4.1. Meta-Heuristic Algorithm 37 2.5. Summary 43 CHAPTER III PAVEMENT PERFORMANCE MASTER CURVE 44 3.1. Introduction 44 3.2. Data Collection 46 3.3. PCI Calculation 47 3.4. Pavement Performance 54 3.4.1. Data Cleaning 54 3.4.2. Performance Model 57 3.5. Non-Linear Programming in Pavement Performance Prediction 60 3.6. Pavement Performance Prediction Error 63 3.7. Summary 64 CHAPTER IV OPTIMIZATION OF PAVEMENT M&R STRATEGY 65 4.1. Introduction 65 4.2. Problem Definition 66 4.3. Multi-Objective Maintenance Optimization 68 4.3.1. Pavement Performance Master Curve 68 4.3.2. Strategy Cost 69 4.3.3. Pavement Quality 69 4.3.4. Model Development Process 70 4.3.5. Encoding 71 4.4. Non-Dominated Sorting Genetic Algorithm (NSGA-II) 74 4.4.1. Initialization 76 4.4.2. Selection 76 4.4.3. Crossover 77 4.4.4. Mutation 77 4.4.5. NSGA-II Parameter 78 4.5. Multi-Objective Particle Swarm Optimization (MOPSO) 78 4.5.1. Initialization 80 4.5.2. Fitness Evaluation 81 4.5.3. Update Position 81 4.5.4. Velocity and Position Update 81 4.5.5. Crowding Distance Assignment 81 4.5.6. Update the Particle Velocities and Positions 81 4.5.7. Mutation 82 4.5.8. MOPSO Parameter 82 4.6. Performance Metric 83 4.6.1. Hypervolume 83 4.7. Summary 84 CHAPTER V RESULT AND CASE STUDY 85 5.1. Result 85 5.1.1. Pavement Performance Prediction 85 5.1.2. Algorithm Comparison Solutions 89 5.1.3. Performance Metric 102 5.2. Case Study 103 5.2.1. Case 1: Minimum Cost 104 5.2.2. Result for Case 1 104 5.2.3. Case 2: Maximum Condition 105 5.2.4. Result for Case 2 105 5.2.5. Case 3: Tools and Resource Availability 106 5.2.6. Result for Case 3 106 5.2.7. Case 4: Pavement Condition 108 5.2.8. Result for Case 4 108 5.3. Summary 110 CHAPTER VI : CONCLUSIONS AND RECOMMENDATIONS 111 6.1. Conclusions 111 6.2. Recommendations 111 REFERENCES 113 APPENDIX 1A FUTURE CONDITION OF PAVEMENT AFTER M&R APPLICATION 122 APPENDIX 1B NSGA-II MATLAB CODE 142 APPENDIX 1C MOPSO MATLAB CODE 152 APPENDIX 2 MASTER CURVE PREDICTION 162 APPENDIX 3A NSGA-II STRATEGY, COST, AND PCI SUMMARY 166 APPENDIX 3B MOPSO STRATEGY, COST, AND PCI SUMMARY 172 APPENDIX 4A NSGA-II STRATEGIY DETAILS 177 APPENDIX 4B MOPSO STRATEGIY DETAILS 182 APPENDIX 4C NSGA-II PAVEMENT PERFORMANCE DETAILS 187 APPENDIX 4D MOPSO PAVEMENT PERFORMANCE DETAILS 192

    Abaza, K. A., Ashur, S. A., & Al-Khatib, I. A., 2004, "Integrated Pavement Management System with a Markovian Prediction Model," Journal of Transportation Engineering, Part B: Pavements, Vol. 130, No. 1, pp. 24-33.
    Abo-Hashema, M., Abdel Samad, A., Al-Zaroni, Y., et al., "Integrating Pavement Maintenance Management Practices and Geographic Information System in Al Ain City, UAE," in Third Gulf Conference on Roads (TGCR06), Muscat, 2006, pp. 279-287.
    Aderinlewo, O., 2016, "Comparative Assessment of Road Rating Systems," Journal of Engineering Studies Research, Vol. 22, No. 2, pp. 7-14.
    Ahmed, K., Al-Khateeb, B., & Mahmood, M., 2019, "Application of Chaos Discrete Particle Swarm Optimization Algorithm on Pavement Maintenance Scheduling Problem," Cluster Computing, Vol. 22, pp. 4647-4657.
    Al-Rubaee, R. H., Shubber, A. A., & Khaleefah, H. S., "Evaluation of Rigid Pavement using the Pavement Condition Index: A Case Study," in IOP Conference Series: Materials Science and Engineering, 2020, vol. 737, no. 1, p. 012128: IOP Publishing.
    Ali, H. A., & Tayabji, S. D., 1998, "Evaluation of Mechanistic-Empirical Performance Prediction Models for Flexible Pavements," Transportation Research Record, Vol. 1629, No. 1, pp. 169-180.
    Almuhanna, R. R., Ewadh, H. A., & Alasadi, S. J., 2018, "Using PAVER 6.5. 7 and GIS Program for Pavement Maintenance Management for Selected Roads in Kerbala City," Case Studies in Construction Materials, Vol. 8, pp. 323-332.
    Archilla, A. R., & Madanat, S., 2000, "Development of a Pavement Rutting Model from Experimental Data," Journal of Transportation Engineering, Vol. 126, No. 4, pp. 291-299.
    ASTM. (2015). Standard Practice for Computing International Roughness Index of Roads from Longitudinal Profile Measurements. In (Vol. E1926-08). West Conshohocken, PA: ASTM International.
    ASTM. (2016). Standard Practice for Roads and Parking Lots Pavement Condition Index Surveys. In (Vol. D6433-16). West Conshohocken, PA, USA: ASTM International.
    Carey, W., & Irick, P., 1960, "The Pavement Serviceability-Performance Concept: Highway Research Board Bulletin, 250," National Research Council, Washington, DC, Vol.
    Chen, C., Flintsch, G., & Al-Qadi, I., "Fuzzy Logic-Based Life-Cycle Costs Analysis Model for Pavement and Asset Management," in 6th International Conference on Managing Pavements, 2004, pp. 19-24: Citeseer.
    Chen, D., & Mastin, N., 2016, "Sigmoidal Models for Predicting Pavement Performance Conditions," Journal of Performance of Constructed Facilities, Vol. 30, No. 4, pp. 04015078.
    Chikezie, C. U., Olowosulu, A. T., & Abejide, O. S., 2013, "Multiobjective Optimization for Pavement Maintenance and Rehabilitation Programming using Genetic Algorithms," Archives of Applied Science Research, Vol. 5, No. 4, pp. 76-83.
    Coello, C. C., 2006, "Evolutionary Multi-objective Optimization: A Historical View of the Field," IEEE Computational Intelligence Magazine, Vol. 1, No. 1, pp. 28-36.
    Coenen, T., & Golroo, A., 2017, "A Review on Automated Pavement Distress Detection Methods," Cogent Engineering, Vol. 4, No. 1, pp. 1374822.
    Di Mino, G., Di Liberto, C., Di Noto, F., et al., "A Multi-objective Approach Based on the Genetic Algorithm Technique for Road Pavement Maintenance," in Vol. 1 of Proc., 4th Int. SIIV Congress Advances in Transport Infrastructures and Stakeholders Expectations, 2007, pp. 1-17.
    El-Diraby, T., Kinawy, S., & Piryonesi, S. M., 2017, "A Comprehensive Review of Approaches Used by Ontario Municipalities to Develop Road Asset Management Plans," Transportation Research Board 96th Annual MeetingTransportation Research Board, Vol., No. 17-00281.
    Elhadidy, A., El-Badawy, S., & Elbeltagi, E., 2021, "A Simplified Pavement Condition Index Regression Model for Pavement Evaluation," International Journal of Pavement Engineering, Vol. 22, No. 5, pp. 643-652.
    Elhadidy, A., Elbeltagi, E., & Ammar, M., 2015, "Optimum Analysis of Pavement Maintenance using Multi-Objective Genetic Algorithms," HBRC Journal, Vol. 11, No. 1, pp. 107-113.
    Elhadidy, A., Elbeltagi, E., & El-Badawy, S., 2020, "Network-Based Optimization System for Pavement Maintenance Using a Probabilistic Simulation-Based Genetic Algorithm Approach," Journal of Transportation Engineering, Part B: Pavements, Vol. 146, No. 4.
    Ferreira, A., Picado-Santos, L., & Antunes, A., "Pavement Performance Modelling: State of the Art," in Proceedings of Seventh International Conference on Civil and Structural Engineering Computing, 1999, pp. 157-264: Civil-Comp Press Oxford.
    Ferreira, A., Picado-Santos, L., & Antunes, A., 2002, "A Segment-Linked Optimization Model for Deterministic Pavement Management Systems," International Journal of Pavement Engineering, Vol. 3, No. 2, pp. 95-105.
    Finn, F., Peterson, D., & Kulkarni, R., 1990, "AASHTO guidelines for pavement management systems," National Cooperative Highway Research Program Final Report, Vol., pp. 20-27.
    Garcia-Diaz, A., & Riggins, M. (1984). Serviceability and Distress Methodology for Predicting Pavement Performance.
    Gupta, A., Kumar, P., & Rastogi, R., 2014, "Critical Review of Flexible Pavement Performance Models," KSCE Journal of Civil Engineering, Vol. 18, pp. 142-148.
    Haas, R., Hudson, W. R., & Zaniewski, J. P. (1994). Modern Pavement Management.
    Hajj, E. Y., Loria, L., Sebaaly, P. E., et al., 2011, "Optimum Time for Application of Slurry Seal to Asphalt Concrete Pavements," Vol. 2235, No. 1, pp. 66-81.
    Hasan, A., Tabassum, K., Kabir, A., et al., 2019, "Maintenance and Possible Remedy for Pavement Distress in Flexible Pavement using Pavement Condition Rating," World, Vol. 4, pp. 27-34.
    Institute, A. (1983). Asphalt Overlays for Highway and Street Rehabilitation: Asphalt Institute.
    Institute, A. (1996). Asphalt in Pavement Maintenance MS-16. Research Park Drive, USA.
    Javed, F., 2010, "Integrated Prioritization and Optimization Approach for Pavement Management," Vol.
    Karim, F., Rubasi, K., & Saleh, A., 2016, "The Road Pavement Condition Index (PCI) Evaluation and Maintenance: A Case Study of Yemen," Organization, Technology Management in Construction: An International Journal, Vol. 8, No. 1, pp. 1446-1455.
    Khavandi, A., & Mohammadi, H., 2018, "Multiobjective Optimization in Pavement Management System using NSGA-II Method," Journal of Transportation Engineering, Part B: Pavements, Vol. 144, No. 2, pp. 04018016.
    Kheirati, A., & Golroo, A., 2022, "Machine Learning for Developing a Pavement Condition Index," Automation in Construction, Vol. 139, pp. 104296.
    Kırbaş, U., & Karaşahin, M., 2016, "Performance Models for Hot Mix Asphalt Pavements in Urban Roads," Construction Building Materials, Vol. 116, pp. 281-288.
    Loprencipe, G., & Pantuso, A., 2017, "A Specified Procedure for Distress Identification and Assessment for Urban Road Surfaces Based on PCI," Coatings, Vol. 7, No. 5, pp. 65.
    Madanat, S., 1993, "Incorporating Inspection Decisions in Pavement Management," Journal of Transportation Engineering, Vol. 27, No. 6, pp. 425-438.
    Mahmood, M., Mathavan, S., & Rahman, M., 2018, "A Parameter-free Discrete Particle Swarm Algorithm and its Application to Multi-objective Pavement Maintenance Schemes," Swarm Evolutionary Computation, Vol. 43, pp. 69-87.
    Mahmood, M., Rahman, M., & Mathavan, S., "Multi-Types of Flexible Pavement Deterioration Prediction Models," in 2020 6th International Engineering Conference “Sustainable Technology and Development"(IEC), 2020, pp. 7-12: IEEE.
    Mamlouk, M. S., & Zaniewski, J. P., 2001, "Optimizing Pavement Preservation: An Urgent Demand for Every Highway Agency," International Journal of Pavement Engineering, Vol. 2, No. 2, pp. 135-148.
    Mathew, B., & Isaac, K., 2014, "Optimisation of Maintenance Strategy for Rural Road Network using Genetic Algorithm," International Journal of Pavement Engineering, Vol. 15, No. 4, pp. 352-360.
    Matin, A., Nezafat, R., & Golroo, A., 2017, "A Comparative Study on using Meta-Heuristic Algorithms for Road Maintenance Planning: Insights from Field Study in a Developing Country," Journal of Traffic Transportation Engineering, Vol. 4, No. 5, pp. 477-486.
    Medina, J., Zalghout, A., Gundla, A., et al., 2021, "Use of Time–Temperature Superposition Principle to Create Pavement Performance Master Curves and Relate Pavement Condition Index and International Roughness Index," Transportation Research Record, Vol. 2675, No. 9, pp. 972-983.
    Miller, J., & Bellinger, W. (2003). Distress Identification Manual for the Long-Term Pavement Performance Program. Retrieved from
    Onyango, M., Merabti, S. A., Owino, J., et al., 2018, "Analysis of Cost Effective Pavement Treatment and Budget Optimization for Arterial Roads in the City of Chattanooga," Frontiers of Structural Civil Engineering, Vol. 12, pp. 291-299.
    Park, K., Thomas, N., & Wayne, L., 2007, "Applicability of the International Roughness Index as a Predictor of Asphalt Pavement Condition," Journal of Transportation Engineering, Vol. 133, No. 12, pp. 706-709.
    Perera, R., Kohn, S., & Rada, G., 2002, "LTPP Manual for Profile Measurements Operational Field Guidelines: Version 4.0," Vol.
    Prozzi, J. (2001). Modeling Pavement Performance by Combining Field and Experimental Data: University of California, Berkeley.
    Prozzi, J., & Madanat, S., 2004, "Development of Pavement Performance Models by Combining Experimental and Field Data," Journal of Infrastructure Systems, Vol. 10, No. 1, pp. 9-22.
    Pulugurta, H., Shao, Q., Chou, Y. J. J. o. S., et al., 2009, "Pavement Condition Prediction using Markov Process," Vol. 12, No. 5, pp. 853-871.
    Ragnoli, A., De Blasiis, M., & Di Benedetto, A., 2018, "Pavement Distress Detection Methods: A Review," Infrastructures, Vol. 3, No. 4, pp. 58.
    Rejani, V., Sunitha, V., Mathew, S., et al., 2022, "A Network Level Pavement Maintenance Optimisation Approach deploying GAMS," International Journal of Pavement Research Technology, Vol. 15, No. 4, pp. 863-875.
    Santana, R. A., Pontes, M. R., & Bastos-Filho, C. J., "A Multiple Objective Particle Swarm Optimization Approach using Crowding Distance and Roulette Wheel," in 2009 Ninth International Conference on Intelligent Systems Design and Applications, 2009, pp. 237-242: IEEE.
    Santos, J., & Ferreira, A., 2012, "Pavement Design Optimization Considering Costs and Preventive Interventions," Journal of Transportation Engineering, Vol. 138, No. 7, pp. 911-923.
    Shah, Y., Jain, S., Tiwari, D., et al., 2013, "Development of Overall Pavement Condition Index for Urban Road Network," Procedia-Social Behavioral Sciences, Vol. 104, pp. 332-341.
    Shahin, & Walther, J. (1990). Pavement Maintenance Management for Roads and Streets using the PAVER System. Retrieved from
    Shahin, M. (2005). Pavement Management for Airports, Roads, and Parking Lots (Vol. 501): Springer.
    Shahin, M., & Kohn, S. D. (1979). Development of a Pavement Condition Rating Procedure for Roads, Streets, and Parking Lots. Volume I. Conditions Rating Procedure. Retrieved from
    Shahnazari, H., Tutunchian, M., Mashayekhi, M., et al., 2012, "Application of Soft Computing for Prediction of Pavement Condition Index," Journal of Transportation Engineering, Vol. 138, No. 12, pp. 1495-1506.
    Shtayat, A., Moridpour, S., Best, B., et al., 2022, "An Overview of Pavement Degradation Prediction Models," Journal of Advanced Transportation, Vol. 2022.
    Sidess, A., Ravina, A., & Oged, E., 2022, "A Model for Predicting the Deterioration of the International Roughness Index," International Journal of Pavement Engineering, Vol. 23, No. 5, pp. 1393-1403.
    Smith, R., Darter, M. I., & Herrin, S. M., 1979, "Highway Pavement Distress Identification Manual," Vol.
    Sotil, A., & Kaloush, K., "Development of Pavement Performance Models for Delhi Township, Ohio Pavement Management System," in Compendium of Papers CD-ROM 83rd Annual Meeting of the Transportation Research Board, 2004.
    Sun, Y., Hu, M., Zhou, W., et al., 2020, "Multiobjective Optimization for Pavement Network Maintenance and Rehabilitation Programming: A Case Study in Shanghai, China," Mathematical Problems in Engineering, Vol. 2020, pp. 1-11.
    Tedeschi, A., & Benedetto, F., 2017, "A Real-Time Automatic Pavement Crack and Pothole Recognition System for Mobile Android-Based Devices," Advanced Engineering Informatics, Vol. 32, pp. 11-25.
    Tzeng, J. Y., "Decision-supporting Model for Pavement Maintenance Scheduling," National Taiwan University of Science and Technology, 2019.
    Vásquez-Varela, R, L., García-Orozco, et al., 2021, "Applied Metaheuristic Optimization in Asphalt Pavement Management," Ciencia e Ingeniería Neogranadina, Vol. 31, No. 2, pp. 75-92.
    Witczak, M., & Bari, J., 2004, "Development of a Master Curve (E*) Database for Lime Modified Asphaltic Mixtures," Arizona State University Research Report, Tempe, AZ, Vol.
    Witczak, M., Kaloush, K., Pellinen, T., et al., 2002, "NCHRP Report 465 Simple Performance Test for Superpave Mix Design," National Cooperative Highway Research Program Report, Vol.
    Wolters, A., Zimmerman, K., Schattler, K., et al., 2011, "Implementing Pavement Management Systems for Local Agencies," Vol.
    Wu, K. (2015). Development of PCI-based Pavement Performance Model for Management of Road Infrastructure System: Arizona State University.
    Zitzler, E. (1999). Evolutionary Algorithms for Multi-objective Optimization: Methods and Applications (Vol. 63): Shaker Ithaca.

    QR CODE