Seasonal furrow irrigation model with genetic algorithms (OPTIMEC)

A seasonal furrow irrigation model based on the concept of a comprehensive irrigation system is implemented using a Visual Basic program, OPTIMEC (ECo nomic OPTIMization in Spanish). From a set of climatological, soil, furrow geometry and crop data for sloping and run-off free furrows, OPTIMEC determ ines a quasi-optimum irrigation season calendar based on economic profit ma ximization. The model features four components: a soil moisture model, an i rrigation hydraulic model, a crop yield model and an economic optimization module. This module uses a heuristic technique, the genetic algorithm (GA), to find a quasi-global optimum combination of irrigation events (defined b y irrigation date, cut-off time and inflow rate) that maximizes net profit. GAs are based on the laws of natural selection and can be applied to many complex problems that are difficult to solve using traditional techniques. The problem stated herein is to find the best combination of weekly irrigat ion events during the season. A maximization approach based on traditional optimization technique is not easy due to the difficulties in establishing an explicit function relating profit, water depth and flow rate. This disad vantage can be overcome using GAs. A field example is used to illustrate mo del options, particularly the analysis capabilities of the optimization app roach. (C) 2001 Elsevier Science B.V. All rights reserved.