I. Context

Logistics optimization remains a major challenge for companies worldwide.

Efficient distribution of goods directly impacts operational costs, customer satisfaction, and environmental footprint.

Logistics-db9279223e6c4ccbbdd7b891f20a056e.jpg


Among the various optimization problems, vehicle routing problems (VRP) occupy a central place.

Source: Dynamic Vehicle Routing Solution in the Framework of Nature-Inspired Algorithms, Omprakash Kaiwartya, 2015

Source: Dynamic Vehicle Routing Solution in the Framework of Nature-Inspired Algorithms, Omprakash Kaiwartya, 2015

Each industrial sector introduces its own specific constraints.

Depending on the sector (transportation, healthcare, agriculture, e-commerce, supply-chain, …)


II. Our Problem

  1. Multi Depots : Vehicles start from and return to multiple different warehouses or hubs instead of just one central location.
  2. Multiple Trips: The vehicles can do more than one route.
  3. Capacitated: The vehicles have a limited carrying capacity of the goods that must be delivered.
  4. Multi Products: The fleet must deliver multiple distinct categories of products to a set of stations.
  5. Asymmetric Demand: A single customer might request a large volume of Product A but a tiny fraction of Product B.
  6. Heterogeneous Fleet: The fleet contains different types of vehicles with varying capacities.
  7. Split deliveries: Each customer can be visited by multiple vehicles, provided the total delivered quantity satisfies their exact demand.

But ! 🤔

This didn’t apply to petroleum products distribution.

According to experts and researchs…

oil_trading.jpg


gresik-jawa-timur-indonesia-june-600w-2795266559.webp

0cbf93fd-cde8-4dc8-8b94-c8c66b61b802_25ae05b3.jpg


Conclusion I

It is clear that the problem exists in one way or another.