Thesis/Capstone
Publication Date
Authored by
Frances Gremillion, Jesus Guajardo
Abstract

As a result of the COVID-19 pandemic, the ecommerce share of retail has grown at an accelerated rate, increasing the number of home deliveries and delivery speed expectation from customers. Moreover, demand variability over the year and delivering a wide variety of products in terms of weight and volume has increased the last mile delivery cost for most companies. We developed this capstone project for one of the biggest retailers in Mexico, Coppel. Our work is focused on creating a strategic tool that allows our sponsor company to define the optimal fleet composition for their last mile delivery operation at each logistic facility, and to formulate an allocation strategy for their different order types. To find the optimal solution in terms of cost, we built a combination knapsack & bin packing model, with aggregate planning. To see how level of service, defined as the delivery speed, and demand variability over the time impacts cost and CO2 emissions, we selected 3 different regions, which are Culiacán, Tecamac, and Monterrey. These three regions were selected, as they cover most of the characteristics of Coppel’s last mile operation. Our results indicate that it is financially beneficial for Coppel to reassess their order allocation restrictions and the usage of third-party, for both full truck rentals and small parcel carriers.

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