In recent years, e-commerce has become widespread in society, and the
logistics of product delivery is a crucial pillar for this market to maintain
a high level of service and remain advantageous for consumers choosing to
make purchases online. The present work aims to study the problem of last-mile vehicle routing for e-commerce deliveries and apply an Iterated Local
Search (ILS) metaheuristic to optimize the routing of parcels in a Brazilian e-commerce company. With the objective of finding routes with the lowest cost
for the deliveries, this study proposes an extension to the Vehicle Routing
Problem with Occasional Drivers (VRPOD), considering a heterogeneous
fleet and occasional drivers handling multiple deliveries. For the methodology
application, data provided by an e-commerce company are used, and they
are properly anonymized to prevent the identification of the company and
its clients, respecting ethical principles. A total of 121 instances are used,
ranging from the smallest with one vertex to the largest with 344. The results of
the proposed model are presented in two scenarios: firstly, considering routing
without the use of occasional drivers, and secondly, considering the availability
of occasional drivers for some routes. Both scenarios are compared with the
routes generated by the current router used in the company, and preliminary
results indicate that without the use of occasional drivers, the proposed ILS
obtains better solutions in 53.72 percent of the instances, and when occasional drivers
are incorporated into the route, improvements occur in 76.03 percent of the instances.
The utilization of occasional drivers also provides a 10.30 percent reduction in the
average routing cost.
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