Abstract
Irrigation is the artifcial employment of water to the plants which is used to assist in the growing of agricultural crops. There are several methods of irrigation that differ in how the water is distributed between fields. In fact irrigation systems can be classified into two main categories: gravity irrigation and pressurized irrigation. The allocation of water to the fields is done either collectively or individually. Whatever the used irrigation technique, the goal is to have a well-designed irrigation system. This research applies the metaheuristic method of ant colony optimization (ACO) to design an optimal irrigation layout. The proposed approach uses ACO rules to generate the possible links between fields which distribute water to farmers. And the algorithm ant system was applied to find the optimal link.
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Dorigo, M., Stützle, T.: Ant Colony Optimization. MIT Press Cambridge, London (2004)
Deneubourg, J.L., Aron, S., Goss, S., Pasteels, J.M.: The self-organizing exploratory pattern of the argentine ant. J. lnsect Behav. 3(2), 159–168 (1990)
Dorigo, M.: Optimization, learning and natural algorithms (in Italian). Ph.D. Thesis, Department of Electronics and Polytechnic of Milan, Italy (1992)
Bullnheimer, B., Strauss, C.: A new rank based version of the ant system-A computational study. In: Adaptive Information Systems and Modelling in Economics and Management Science (1997)
Stützle, T., Hoos, H.: Max-Min ant system. Future Gener. Comput. Syst. 16(9), 889–914 (2000)
Dorigo, M., Gambardella, L.: Ant colony system: a cooperative learning approach to the traveling salesman problem. IEEE Trans. Evol. Comput. 1(1), 53–66 (1997)
Dorigo, M., Gambardella, L.: Ant-Q: A reinforcement learning approach to the traveling salesman problem (1997)
Gambardella, L., Dorigo, M.: Has-sop: Hybrid ant system for the sequential ordering problem. Technical Report IDSIA 11–97 (2000)
Maniezzo, V., Colorni, A.: The ant system applied to the quadratic assignment problem. IEEE Trans. Knowl. Data Eng. 11(5), 769–778 (1999)
Solnon, C.: Combining two pheromone structures for solving the car sequencing problem with ant colony optimization (2008)
Fenet, S., Solnon, C.: Searching for maximum cliques with ant colony optimization (2003)
Zapata, N., Playan, E., Lecina, S.: From on-farm solid-set sprinkler irrigation design to collective irrigation network design in windy areas. Agric. Water Manag. 87(2), 187–199 (2007)
González, P.M., Poyato, C., Díaz, R.: Optimization of irrigation scheduling using soil water balance and genetic algorithms. Water Resour. Manage. 30(8), 2815–2830 (2016)
Carríon, F., Sanchez-Vizcaino, J., Moreno, M.: Optimization of groundwater abstraction system and distribution pipe in pressurized irrigation systems for minimum cost. Irrig. Sci. 34(2), 145–159 (2016)
García, F., Montesinos, P., Díaz, J.: Energy cost optimization in pressurized irrigation networks. Irrig. Sci. 34(1), 1–13 (2015)
Sonit, A., Hemlata, K.: Optimization of water use in summer rice through drip irrigation. J. Soil Water Conserv. 14(2), 157–159 (2015)
Izquiel, A., Carriíon, P., Moreno, M.A.: Optimal reservoir capacity for centre pivot irrigation water supply Maize cultivation in Spain. Biosyst. Eng. 135, 61–72 (2015)
Mariano, C.E., Morales, E.: A multiple objective ant-Q algorithms for the design of water distribution irrigation network (1999)
Tu, Q., Li, H., Wang, X., Chen, C.: Ant colony optimization for the design of small scale irrigation systems. Water Resour. Manage. 29(7), 2323–2339 (2015)
Duc, C.H.N., Holger, R.M., Graeme, C.D., James, C.A.: Framework for computationally efficient optimal crop and water allocation using ant colony optimization. Environ. Model. Softw. 76, 37–53 (2016). Elsevier
Kumar, D.N., Reddy, M.J.: Ant colony optimization for multi-purpose reservoir operation. Water Resour. Manage. 20, 879–898 (2006). Elsevier
Nguyen, T.D., Do, P.T.: An ant colony optimization algorithm for solving group steiner problem. In: IEEE Fifth International Conference Communications and Electronics (ICCE), pp. 244–249 (2014)
Dorigo, M., Maniezzo, V., Colorni, A.: An investigation of some properties of an ant algorithm. In: Appeard in Proceeding of the Parallel Problem Solving from Nature Conference, Brussels, Belguim. Elsevier (1992)
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Marouane, S., Alahmari, F., Akaichi, J. (2018). Ant Colony Optimization Approach for Optimizing Irrigation System Layout: Case of Gravity and Collective Network. In: De Pietro, G., Gallo, L., Howlett, R., Jain, L. (eds) Intelligent Interactive Multimedia Systems and Services 2017. KES-IIMSS-18 2018. Smart Innovation, Systems and Technologies, vol 76. Springer, Cham. https://doi.org/10.1007/978-3-319-59480-4_32
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DOI: https://doi.org/10.1007/978-3-319-59480-4_32
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