A practical surface irrigation design based on fuzzy logic and meta-heuristic algorithms

Abstract

Nowadays improving the method of design in agriculture using new technologies is a common issue. Irrigation system plays an important role in productivity and some new methods are proposed in this domain. As most of the proposed models are more focused on performance criteria, their obtained design have problems in terms of practicality and feasibility. This paper presents a simulation-optimization model for designing a surface irrigation system. The main innovation of the proposed model is its special focus on the feasibility in real issues. It gives an optimal and feasible surface irrigation system by fuzzy expert systems and meta-heuristic optimization algorithms. Five fuzzy expert systems analyze the feasibility level of the obtained irrigation system using inference rules which are proposed by expert farmers, and 10 meta-heuristic optimization algorithms optimize the irrigation system based on the fuzzy expert systems outputs. Experiments were performed to evaluate the proposed model. Parameters of 14 fields with different irrigation systems were used in the experiments. The experimental results were re-evaluated by two well-known simulator software programs as SIRMOD and WinSRFR, the obtained results validate the performance of the simulation part of the model. The results of the experiments were compared with the results of three other simulation-optimization models. It was found that the designs presented by the proposed model provide more favorable results in terms of quality, practicality and labor. The designs provided by the proposed model on average reduce labor by 10%, increase practicality by 9% and improve performance by 13%.