Ant Colony Optimization for the Design of Small-Scale Irrigation Systems

摘要: The optimal design of sprinkler irrigation systems is a complicated nonlinear programming problem that related to the performance system and meanwhile an economic farmers in developing countries. Ant colony optimization (ACO), meta-heuristic algorithm with strategies inspired by foraging ants, was considered. Exactly Cycle System proposed solve this problem. ACO compared Genetic Algorithm (GA), results were further validated field tests on four small-scale systems. In model, objective function minimizing specific energy consumption subject constraints pipe diameters, number sprinklers working pressure end along pipeline pump-pipeline cooperation conditions. ACO, head loss between adjacent introduced heuristic represent distance two cities Travelling Salesman Problem (TSP). And fitness composed dealt penalty taken instead total length route pheromone updating. indicate has been decreased average 12.45 % through 10.27 GA 11.27 from initial configurations uniformities higher than 75 tests. implementation outperforms genetic efficiency reliability especially larger may provide promising approach for