Abstract:

Firstly, aiming at the premature convergence problem of Invasive Weed Optimization (IWO) algorithm,a hybrid algorithm of Bee Colony and Invasive Weed Optimization (BCIWO) is proposed by introducing the optimization mechanism of Artificial Bee Colony (ABC) algorithm. Every individual in the weed colony is mutated by employed bees’ search behavior and the global best individual is mutated by onlookers’ search method in this improved algorithm. The better result of mutation is used to replace the original individual.Those improve the convergence speed and the accuracy of IWO.Then the optimal performance of BCIWO is verified by test functions.Finally,the new algorithm is applied into the irrigation schedule optimization problem,thus providing a promising way to allocate irrigation water.

Key words: swarm intelligence;invasive weed optimization algorithm;artificial bee colony algorithm;genetic algorithm;Jesen model;optimized irrigation