It is well accepted that maintenance is a critical component during service life of pavement. One of the ways to enhance pavement life of deteriorating pavement is resurfacing. Various optimization procedures currently used are simplified models for finding optimal frequency and intensity of resurfacing activity. Thus, these models are unable to handle complicated scenarios like changes in cost components, interest rates and inflation rates during the life of the pavement. In this research, an improved artificial bee colony algorithm approach is proposed to solve pavement resurfacing problem. This approach is based on collective behaviour of bees while searching for food source. In this approach, various scenarios are generated as possible solution, optimality of each case is evaluated, and the information thus generated is compared with previously stored values. This process is continued until optimality is reached. The effectiveness of proposed method is demonstrated by solving a numerical example reported in literature. The results indicate better resurfacing trajectories can be obtained (in comparison to closed form solution) with little computational effort.