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- W2972010347 abstract "The scarcity of water is a growing problem worldwide. The increasing use of water in industrial, urban, and agricultural applications together with the continuous increase in population require the proposal of efficient solutions. In the case of agricultural use, it is necessary to not only maximize the economic benefits, but also to establish optimal waterâsaving crop planning, especially for waterâdeficient regions. Due to the multiâobjective nature of these problems, the decisionâmaking process is complex. Fortunately, the increase in computational resources available in recent years has allowed researchers to develop efficient computational algorithms to deal with real and complex optimization problems, including agricultural ones. In particular, multiâobjective evolutionary algorithms (MOEAs) are known for their ability to optimize several objective functions simultaneously to provide a representative set of the Pareto front, which is a set of problem solutions representing a tradeâoff between the best values of each of the objectives. This article proposes solving a multiâobjective crop planning problem using two Paretoâbased MOEAs. Results obtained when solving this problem using real data collected from a large number of greenhouses in Spain to show the advantages of using these multiâobjective approaches." @default.
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- W2972010347 date "2011-01-01" @default.
- W2972010347 modified "2023-09-26" @default.
- W2972010347 title "Multiâobjective crop planning using paretoâbased evolutionary algorithms" @default.
- W2972010347 hasPublicationYear "2011" @default.
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