Optimisation of takeaway delivery routes considering the mutual satisfactions of merchants and customers

• A vehicle routing optimization model considering dual satisfaction is established. • An improved GA with forward continuous crossover and differential mutation is given. • A case study is conducted to compare the improved GA with the two algorithms. To solve a series of problems (including high cost and delivery delay) during takeaway delivery, a model for the vehicle routing problem (VRP) during goods pickup and delivery is developed by considering constraints such as the capacity of delivery vehicles, delivery mileage and time window. The model is constructed by transforming the satisfactions of merchants and customers into a penalty function and aiming to minimise the total delivery cost. As for the drawbacks in a conventional genetic algorithm (CGA), such as a low convergence rate and locally optimum solutions, an improved GA (IGA) is designed by separately using the insertion heuristic algorithm to construct initial solutions and introducing the forward continuous crossover and differential mutation strategies. On the one hand, the numerical analysis and test of weights indicate that the model can reduce the delivery cost of enterprises offering takeaway service and improve satisfactions of merchants and customers. It verifies that reasonably considering satisfactions of merchants and customers during vehicle routing is conducive to cost-reduction and increased efficiency of enterprises. On the other hand, a simulation is conducted to compare and analyse various algorithms based on two different scales of test examples, which validates the proposed algorithm as effective. The study provides a theoretical basis and decision reference for enterprises offering takeaway service to improve delivery efficiency and competitiveness.