An improved artificial bee colony algorithm for pavement resurfacing problem

Abstract Pavement resurfacing is a maintenance activity that is undertaken to enhance the service life of pavement. This pavement resurfacing activity involves laying a new layer of asphalt concrete over existing pavement after certain time. Due to engineering factors, economic variables and uncertainty in forecasting, the pavement resurfacing decision process is a complicated activity. Various optimization approaches currently used are simplified models for finding optimal frequency and resurfacing intensity within pavement maintenance framework. In this research, artificial bee colony algorithm is proposed to solve this pavement resurfacing optimization problem. This algorithm mimics the collective behaviour of bees while searching for nectar. In this approach, various scenarios are generated, optimality of each case is evaluated, and the information thus generated is used in subsequent evaluation until global optimality is reached. The effectiveness of proposed method is demonstrated through a numerical example. The solution obtained is similar to the exact solution reported in literature. The results indicate optimal resurfacing values can be obtained with little computational effort with proposed approach. The main advantage of proposed algorithm is removal of specification of trigger values for maintenance decision.

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