| dc.description.abstract | The advent of e-commerce has revolutionized the retail landscape, offering consumers
unparalleled convenience and access to a myriad of products with just a few clicks.
However, this exponential surge in online shopping has presented a host of logistical
challenges for shipping companies tasked with fulfilling the burgeoning demand. In this
dynamic environment, the efficient management of delivery routes becomes paramount,
with a keen emphasis on optimizing operations to maximize profitability while meeting
stringent weight and timing restrictions. Moreover, the prevalence of order reassignments
within a two-day window adds an additional layer of complexity to the traditional Vehicle
Routing Problem (VRP), necessitating innovative approaches to align theoretical models
with practical realities.
Therefore, this thesis studies the problem by referencing the Mixed-Integer Linear
Programming (MILP) model of Orenstein, Ido, Raviv, Tal, and Sadan, Elad (2019), and
develops a Constraint Programming (CP) model to solve the problem. Data consisting of
over 50 points, including the depot, and 1500 parcels of 3 different sizes are used to run the
CP model. The results produced a detailed delivery plan with a success rate of 88% and the
corresponding costs. Additionally, a sensitivity analysis was conducted to evaluate and
provide recommendations on adjusting the weights in the objective function to achieve
more successful deliveries and cost savings. Finally, the impacts on the environment,
society, and economy when applying the model in practice are analyzed | en_US |
