Applying Ant Colony Optimization for the Decision Support of Green Area Maintenance

Abstract

The maintenance of green areas is important for schools, parks, and recreational areas. But it places a heavy burden on both manpower and budget. In this paper, we apply ant colony optimization (ACO) to search for the minimum gardener manpower requirements and a near-optimal maintenance schedule for the green areas. Unlike other applications of ACO, we grouped the ants into teams to represent gardeners and considered the path of an ant team a schedule solution. We implemented the proposed model using a decision support system called the Garden-Ant. In addition, the feasibility of the model was evaluated on a campus. The results of the evaluation indicated that the proposed model could provide an appropriate maintenance plan, including manpower estimation and an all-inclusive maintenance schedule. Because the complicated calculations are performed by the model instead of by an administrator, the maintenance planning of green areas can be accomplished in an easy and efficient manner.