Simulation of online food ordering delivery strategies using multi-agent system models
Guangyu Zou, Ming Gao, Jiafu Tang, Levent Yılmaz
Abstract
With the rapid development of Online to Offline (O2O) business, millions of transactions each day along with the varying processing time of merchants and the complexity of traffic conditions pose significant challenges to effective and efficient delivery of orders. This paper studies the complex adaptive dynamics of O2O platforms by combining the behaviors of customers, merchants, dispatcher, and couriers in the context of a multi-agent model. Serving as a testbed, the simulation model enables the evaluation of alternative order delivery strategies. Preliminary experimental results show that TSP-based delivery strategy is more efficient than the nearer merchant assignment strategy. As an important property, the larger load capacity of couriers is beneficial to improve the completion rate of orders rather than the completion time. Finally, the experiment using the real road network and the real order data demonstrates the applicability of the proposed multi-agent model of O2O platform in the real scenario.