Carbon Dioxide Minimization in Large-Scale Pavement Network Maintenance Planning

Document Type : Research Article


1 Department of Civil and Environmental Engineering, Amirkabir University of Technology, Tehran, Iran.

2 Amirkabir University of Technology, Tehran, Iran

3 Dep. of Civil Engineering, Amirkabir University of Technology

4 Transportation group, Civil dept, AUT


Choosing an appropriate strategy to maintain pavements has become a significant concern. Recently, pavement agencies tackle large-scale networks, which makes the problem complicated. To prevail in this complexity, utilizing metaheuristic algorithms can be an ideal approach. By increasing the dimension of the problem, the competency of metaheuristic algorithms is by far enhanced. To this end, the water cycle algorithm is applied to solve the problem. In this investigation, two models, including single objective optimization and multi-objective optimization, are taken into consideration. In the single-objective model, the minimization of the network International Roughness Index (IRI) is considered as the objective function. In multi-objective optimization modeling, minimization of the network International Roughness Index and embodied CO2 emission are taken into account simultaneously. Furthermore, a new constraint is considered in the model, which leads to restricting the budget fluctuation in different years of the analysis period. A network, including 79 segments, is the case study of this investigation. The results reveal that the water cycle algorithm is highly qualified to solve the pavement maintenance and rehabilitation problem. According to the results, multi-objective optimization reduces the CO2 emission by 47.2% compared with single-objective modeling. Furthermore, the variation of minimum and maximum costs is less than 20% in the planning horizon.


Main Subjects

[1] France-Mensah, W.J. O’Brien, Budget allocation models for pavement maintenance and rehabilitation: Comparative case study, Journal of Management in Engineering, 34(2) (2018) 05018002.
[2] R. Spielhofer, A. Weninger-Vycudil, M. Oldfield, G. Mladenović, P. Lepert, J. Pohu, H. Litzka, Cross-asset risk assessment on network level, Transport Research Arena Tra2016, 14 (2016) 32-41.
[3] P. Saha, K. Ksaibati, A risk-based optimization methodology for managing county paved roads, in:  The 94th Transportation Research Board Annual Meeting 2015, Citeseer, 2015.
[4] A. Osorio, A. Chamorro, S. Tighe, C. Videla, Calibration and validation of condition indicator for managing urban pavement networks, Transportation Research Record, 2455(1) (2014) 28-36.
[5] S. Woo, H. Yeo, Optimization of pavement inspection schedule with traffic demand prediction, Procedia-Social and Behavioral Sciences, 218 (2016) 95-103.
[6] S. Islam, W.G. Buttlar, Effect of pavement roughness on user costs, Transportation research record, 228(1)5 (2012) 47-55.
[7] C. Torres-Machi, E. Pellicer, V. Yepes, A. Chamorro, Towards a sustainable optimization of pavement maintenance programs under budgetary restrictions, Journal of cleaner production, 148 (2017) 90-102.
[8] M. Hafez, K. Ksaibati, R.A. Atadero, Applying large-scale optimization to evaluate pavement maintenance alternatives for low-volume roads using genetic algorithms, Transportation Research Record, 2672(52) (2018) 205-215.
[9] A. Khavandi Khiavi, H. Mohammadi, Multiobjective optimization in pavement management system using NSGA-II method, Journal of Transportation Engineering, Part B: Pavements, 144(2) (2018) 04018016.
[10] A.V. Moreira, T.F. Fwa, J.R. Oliveira, L. Costa, Coordination of user and agency costs using two-level approach for pavement management optimization, Transportation Research Record, 2639(1) (2017) 110-118.
[11] P. Saha, K. Ksaibati, Optimization model to determine critical budgets for managing pavement and safety: Case study on statewide county roads, Journal of Transportation Engineering, Part A: Systems, 145(2) (2019) 04018088.
[12] N.R. Tayebi, F.M. Nejad, M. Mola, Comparison between GA and PSO in analyzing pavement management activities, Journal of Transportation Engineering, 140(1) (2014) 99-104.
[13] A.G. Matin, R.V. Nezafat, A. Golroo, A comparative study on using meta-heuristic algorithms for road maintenance planning: Insights from field study in a developing country, Journal of Traffic and Transportation Engineering (English Edition), 4(5) (2017) 477-486.
[14] K. Ahmed, B. Al-Khateeb, M. Mahmood, A chaos with discrete multi-objective particle swarm optimization for pavement maintenance, J. Theor. Appl. Inf. Technol, 96(8) (2018) 2317-2326.
[15] T.R. Panda, A.K. Swamy, An improved artificial bee colony algorithm for pavement resurfacing problem, International Journal of Pavement Research and Technology, 11(5) (2018) 509-516.
[16] C. Torres-Machí, A. Chamorro, E. Pellicer, V. Yepes, C. Videla, Sustainable pavement management: Integrating economic, technical, and environmental aspects in decision making, Transportation Research Record, 2523(1) (2015) 56-63.
[17] R.B. Mallick, A. Veeraragavan, Sustainable pavements in India-the time to start is now, New Building Materials and Construction World (NBM&CW) Magazine, 16(3) (2010) 128-140.
[18] C. Torres-Machi, A. Osorio-Lird, A. Chamorro, C. Videla, S.L. Tighe, C. Mourgues, Impact of environmental assessment and budgetary restrictions in pavement maintenance decisions: Application to an urban network, Transportation Research Part D: Transport and Environment, 59 (2018) 192-204.
[19] S. Chan, B. Lane, T. Kazmierowski, W. Lee, Pavement preservation: A solution for sustainability, Transportation research record, 2235(1) (2011) 36-42.
[20] F. Giustozzi, M. Crispino, G. Flintsch, Multi-attribute life cycle assessment of preventive maintenance treatments on road pavements for achieving environmental sustainability, The International Journal of Life Cycle Assessment, 17(4) (2012) 409-419.
[21] P. Lu, D. Tolliver, Pavement treatment short-term effectiveness in IRI change using long-term pavement program data, Journal of transportation engineering, 138(11) (2012) 1297-1302.
[22] M.Y. Shahin, Pavement management for airports, roads, and parking lots, Springer New York, 20.
[23] A. Osorio-Lird, A. Chamorro, C. Videla, S. Tighe, C. Torres-Machi, Application of Markov chains and Monte Carlo simulations for developing pavement performance models for urban network management, Structure and Infrastructure Engineering, 14.
[24] D. Wu, C. Yuan, H. Liu, A risk-based optimization for pavement preventative maintenance with probabilistic LCCA: a Chinese case, International Journal of Pavement Engineering, 18(1) (2017) 11-25.
[25] Iran's Road Maintenance and Transportation Organization." , Access on: Nov, 2018.
[26] C.H. Papadimitriou, On the complexity of integer programming, Journal of the ACM (JACM), 28(4) (1981) 765-768.
[27] A. Sadollah, H. Eskandar, A. Bahreininejad, J.H. Kim, Water cycle algorithm for solving multi-objective optimization problems, Soft Computing, 19(9) (2015) 2587-2603.
[28] Sadollah, H. Eskandar, J.H. Kim, Water cycle algorithm for solving constrained multi-objective optimization problems, Applied Soft Computing, 27 (2015) 279-298.
[29] H. Eskandar, A. Sadollah, A. Bahreininejad, M. Hamdi, Water cycle algorithm–A novel metaheuristic optimization method for solving constrained engineering optimization problems, Computers & Structures, 110 (2012) 151-166.
[30] A. Sadollah, H. Eskandar, H.M. Lee, J.H. Kim, Water cycle algorithm: a detailed standard code, Software X, 5 (2016) 37-43.
[31] Sadollah, H. Eskandar, A. Bahreininejad, J.H. Kim, Water cycle algorithm with evaporation rate for solving constrained and unconstrained optimization problems, Applied Soft Computing, 30 (2015) 58-71.
[32] Q. Dong, B. Huang, Evaluation of effectiveness and cost-effectiveness of asphalt pavement rehabilitations utilizing LTPP data, Journal of Transportation Engineering, 138(6).
[33] V. Yepes, C. Torres-Machi, A. Chamorro, E. Pellicer, Optimal pavement maintenance programs based on a hybrid greedy randomized adaptive search procedure algorithm, Journal of Civil Engineering and Management, 22(4) (2016) 540-550.
[34] Y. Li, S. Madanat, A steady-state solution for the optimal pavement resurfacing problem, Transportation Research Part A: Policy and Practice, 36(6) (2002) 525-535.
[35] Y. Ouyang, S. Madanat, Optimal scheduling of rehabilitation activities for multiple pavement facilities: exact and approximate solutions, Transportation Research Part A: Policy and Practice, 38(5) (2004) 347-365.
[36] J. Chehovits, L. Galehouse, Energy usage and greenhouse gas emissions of pavement preservation processes for asphalt concrete pavements, in:  Proceedings on the 1st International Conference of Pavement Preservation, 2010, pp. 27-42.
[37] M. Onyango, S.A. Merabti, J. Owino, I. Fomunung, W. Wu, Analysis of cost effective pavement treatment and budget optimization for arterial roads in the city of Chattanooga, Frontiers of Structural and Civil Engineering, 12(3) (2018) 291-299.