Simulation-based Algorithm for Determining Best Package Delivery Alternatives under Three Criteria: Time, Cost and Sustainability
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With the significant rise in demand for same-day instant deliveries, several courier services are exploring alternatives to transport packages in a cost- and time-effective, as well as, sustainable manner. Motivated by a real-life case study, this paper focuses on developing a simulation algorithm that assists same-day package delivery companies to serve customers instantly. The proposed recommender system provides the best solution with respect to three criteria: cost, time, and sustainability, considering the variation in travel time and cost parameters. The decision support tool provides recommendations on the best alternative for transporting products based on factors, such as source and destination locations, time of the day, package weight, and volume. Besides considering existing new technologies like electric-assisted cargo bikes, we also analyze the impact of emerging methods of deliveries, such as robots and air taxis. Finally, this paper also considers the best delivery alternative during the presence of a pandemic, such as COVID-19. For the purpose of illustrating our approach, we consider the delivery options in New York City. We believe that the proposed tool is the first to provide solutions to courier companies considering evolving modes of transportation and under logistics disruptions due to pandemic. Keywords: Instant package delivery; Courier services; Simulation algorithm; Recommender system; Emerging technologies; COVID-19 pandemic.
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