Enhanced intelligent water drops with genetic algorithm for multi-objective mixed time window vehicle routing

In the context of addressing the multi-objective vehicle routing problem, a hybrid time window multi-objective vehicle model was established using integer programming and the intelligent water drop algorithm. To overcome the limitation of the intelligent water drop algorithm potentially converging to local optimal solutions, enhancements were proposed through genetic algorithms, particularly by introducing genetic crossover and single-point recombination operators. Subsequently, the intelligent water drop algorithm was refined, and its effectiveness was evaluated through a real-world case study. Comparative analyses were conducted among three algorithms: IWD, GA, and SA. The results demonstrate that the improved algorithm effectively alleviates the common issue of traditional algorithms converging to local optimal solutions. Therefore, an enhanced solution is provided for the discrete hybrid time window problem, achieving superior optimization outcomes.