Implementation of a Genetic Algorithm to Optimize the Distribution of Water in Irrigation of Peruvian Farmland Affected by "El Niño"

Water scarcity and floods produced by "El Niño" are huge impact problems in Peruvian agricultural industry where the increment of water use to irrigate crops forces small producers and farmers in general, to establish a transversal perspective at the time of satisfiability of the water resource for each crop conditioned on demand. In the period of El Niño occurrence (summer in the southern hemisphere), the types of agricultural crops are restricted and only they can be planted according to the climatic conditions and highly specific ground. To achieve the water satisfiability within the control of said crops, it should be performed a risk planning so that profit maximization is achieved, reducing costs from the water availability. Because the problem of satisfiability is the NP-Complete type, it is feasible the use of evolutionary meta-heuristic algorithms such as the genetic algorithms (GA) to obtain a solution under several hard restrictions. This article introduces a genetic algorithm and a comparison of results against a Construction GRASP algorithm under performance constraints, water requirement and distance to the nearest water reservoir as well as the own characteristics such as the cost, crop benefit and the land area to be irrigated. Copyright ISCA.