Cost optimization of pavement thickness design using intelligent search versus linear programming algorithms

Abstract

Road pavement costs expend a significant share of financial resources in road construction, and finding the optimal pavement thickness design with minimal cost remains a concern that can be determined using intelligent search algorithms. This study aims to evaluate the performance of the particle swarm optimization (PSO) algorithm based on Iranian Highway Asphalt Paving (IHAP) Code 234. Thus, using the PSO algorithm, the problem of pavement thickness design was solved numerically, and a simulation–optimization technique was devised. Comparing PSO and the linear algorithms (LP) indicates that PSO is accounted as an optimal pavement thickness design regardless of different ranges of the equivalent single-axle loads (ESALs) and resilient moduli (Mr). Considering the four-layer and three-layer pavement designs revealed that the different bitumen-stabilized bases in the four-layer design are not cost-effective. Moreover, the PSO design resulted in 22–29 percent cost savings at various ESALs and Mr; however, the three-layer design was 23–31 percent less expensive.

Keywords

• Asphalt pavement
• Optimal pavement design
• IHAP design method
• PSO
• Linear programming