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Multi-objective differential evolution application to irrigation planning
In the present study, applicability of Multi-objective Differential Evolution (MODE) in irrigation planning perspective is demonstrated through a case study of Mahi Bajaj Sagar Project, Rajasthan, India. Three objectives, namely, net benefits, agricultural production and labour employment are analysed in the multi-objective environment. Non-dominated alternatives generated by MODE are reduced to a manageable subset with the help of K-means cluster analysis for effective decision making. Optimal number of groups is determined based on the cluster validation indices, namely, Davies–Bouldin and Dunn's. It is concluded that selection of suitable parameters is necessary for effective implementation of above methodologies in real-world planning situations.
Multi-objective differential evolution application to irrigation planning
In the present study, applicability of Multi-objective Differential Evolution (MODE) in irrigation planning perspective is demonstrated through a case study of Mahi Bajaj Sagar Project, Rajasthan, India. Three objectives, namely, net benefits, agricultural production and labour employment are analysed in the multi-objective environment. Non-dominated alternatives generated by MODE are reduced to a manageable subset with the help of K-means cluster analysis for effective decision making. Optimal number of groups is determined based on the cluster validation indices, namely, Davies–Bouldin and Dunn's. It is concluded that selection of suitable parameters is necessary for effective implementation of above methodologies in real-world planning situations.
Multi-objective differential evolution application to irrigation planning
Raju, K. Srinivasa (author) / Vasan, A. (author) / Gupta, Piyush (author) / Ganesan, Karthik (author) / Mathur, Hitesh (author)
ISH Journal of Hydraulic Engineering ; 18 ; 54-64
2012-03-01
11 pages
Article (Journal)
Electronic Resource
English
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