Decision support for the maintenance management of green areas

For schools, parks, and recreational areas, the maintenance of green areas is important, but it places a heavy burden on both manpower and budget. In this paper, we proposed a model to search for the minimum gardener manpower requirements and a near-optimal maintenance schedule for the green areas. Unlike other applications of ant colony optimization, 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.

[1]  Yueh-Min Huang,et al.  Multiprocessor system scheduling with precedence and resource constraints using an enhanced ant colony system , 2008, Expert Syst. Appl..

[2]  Hassan M. Emara,et al.  Using Ant Colony Optimization algorithm for solving project management problems , 2009, Expert Syst. Appl..

[3]  Chang-Shing Lee,et al.  Ontological recommendation multi-agent for Tainan City travel , 2009, Expert Syst. Appl..

[4]  C Y Jim,et al.  Managing Urban Trees and Their Soil Envelopes in a Contiguously Developed City Environment , 2001, Environmental management.

[5]  Sheri Zidenberg-Cherr,et al.  Use of school gardens in academic instruction. , 2005, Journal of nutrition education and behavior.

[6]  Yueh-Min Huang,et al.  Ant colony-based algorithm for constructing broadcasting tree with degree and delay constraints , 2008, Expert Syst. Appl..

[7]  Thomas Stützle,et al.  Ant Colony Optimization Theory , 2004 .

[8]  Joanne Connell,et al.  Managing gardens for visitors in Great Britain: a story of continuity and change , 2005 .

[9]  Marco Dorigo,et al.  Optimization, Learning and Natural Algorithms , 1992 .

[10]  R. J. Kuo,et al.  Mining association rules through integration of clustering analysis and ant colony system for health insurance database in Taiwan , 2007, Expert Syst. Appl..

[11]  Alex Alves Freitas,et al.  Data mining with an ant colony optimization algorithm , 2002, IEEE Trans. Evol. Comput..

[12]  Miguel A. Mariño,et al.  Application of an ant algorithm for layout optimization of tree networks , 2006 .

[13]  Thomas Stützle,et al.  MAX-MIN Ant System , 2000, Future Gener. Comput. Syst..

[14]  Nasser Ghasem-Aghaee,et al.  Text feature selection using ant colony optimization , 2009, Expert Syst. Appl..

[15]  Marco Dorigo,et al.  Ant system: optimization by a colony of cooperating agents , 1996, IEEE Trans. Syst. Man Cybern. Part B.