Sustainable pavement maintenance and rehabilitation planning using the marine predator optimization algorithm
Hamed Naseri, Amir Golroo, Mohammad Shokoohi, Amir H. Gandomi
Abstract
The sustainability of pavement, especially in Maintenance and Rehabilitation (M&R) scheduling, has become an immense concern and has received limited attention in previous studies. Therefore, this study aimed to develop the M&R scheduling optimization based on sustainability. To this end, a novel sustainability index was introduced, in which all the sustainable development aspects were considered, including highway agency cost, environmental impacts, and social effects. A conventional model was used to assess the sustainable model’s effectiveness. Two new constraints are introduced to reduce the budget fluctuation and not to apply the M&R treatments for two consecutive years to make the model practical. On the other hand, highway agencies face large-scale networks, in which the optimization of M&R scheduling has computational complexities. Thus, the novel and powerful metaheuristic algorithm, named Marine Predator Algorithm (MPA), was applied to solve the pavement M&R scheduling problem. A large-scale pavement network, including 110 sections, was analyzed over a 5-year plan as the case study. The results indicated that using the sustainable model rather than the conventional one leads to a 6.5% reduction in CO2 emission. Besides, utilizing the sustainable approach enhances the equity and safety indices by 40.7% and 2.5% compared to the conventional treatment. However, the highway agency cost is increased by 1.1% using the sustainable model.