With the popularization of logistics technology and the improvement of people ' s living standards, the number of chain restaurants with delivery service is increasing continuously due to the convenient service and special discounts. However, the inappropriate management mode and delivery delays often lead to high delivery cost, especially during the peak meal period. Therefore, to solve the problems, two delivery modes, Modern Delivery Mode of Chain Restaurants (MDMCR) and Improved Delivery Mode of Chain Restaurants (IDMCR) were first proposed. IDMCR is an one-stage approach to directly solve the delivery routing problem of multiple branches. Furthermore, we presented an adaptive genetic algorithm for delivery of chain restaurants (AGA-DCR) specifically for IDMCR, which adjusts adaptively the traditional crossover and mutation operations to the fitness of individual and population, therefore, local optimal is avoid. The experiments were conducted with the same dataset to compare different approaches. The results demonstrated that AGA-DCR avoided falling into the local optimal while improved the quality of the solution. Moreover, IDMCR combined with AGA-DCR achieved the best performance, reducing the delivery delay cost by 56.2% compared to MDMCR with GA. Additionally, the optimal delivery routes for chain restaurants were visualized to provide a reference solution for the practical applications.INDEX TERMS adaptive genetic algorithm, chain restaurants delivery, multi-depot vehicle routing problem, vehicle routing.

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