Adaptive Ant Colony Optimization for Solving the Parking Lot Assignment Problem

Terrible traffic conditions and scarcities of parking resources in modern cities make it increasingly difficult for people to find suitable parking spaces, especially for a group of drivers. In order to alleviate traffic pressure, reduce traveling costs and time consumptions, we propose a new parking lot assignment model for group parking. The model not only considers the factors in the traditional parking assignment model, such as driver locations, parking lot capacities, parking time and drivers' preferences, but also includes the variable price scheme and the balance of arrival time issue. To solve the problem, we devise a standard ant colony optimization algorithm, which is further enhanced by using the adaptive strategies. Experimental results show that the proposed algorithms perform better than the previous algorithms in efficacy and efficiency.