Research on Self-Delivery Route Optimization of Takeaway Based on Improved Whale Algorithm

In order to maximize business benefit and customer satisfaction, a multi-objective function model was established to minimize distribution cost, distribution time and maximize customer satisfaction. Firstly, adaptive weight is introduced on the basis of the traditional whale algorithm to improve the optimization ability of the algorithm. Secondly, Lévy flight strategy was used to disturb individual whales to expand the search range of the algorithm. Finally, the random differential evolution strategy is used to disturb the population to avoid the algorithm falling into local optimal. The improved whale algorithm (MOIWOA), standard whale algorithm (MOWOA), non-dominant sorting genetic algorithm (NSGA-II), and standard Grey Wolf optimization algorithm (MOGWO) are compared by examples. The results show that: The improved whale algorithm has better global optimization ability and faster convergence in terms of minimum cost, shortest time and maximum satisfaction, which verifies the effectiveness and stability of the algorithm.