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Cooperation in last mile and freight forwarding issues

Considerations for transforming from end customer to intermediate point of collection

Before defining the concept of cooperative agents, we must contextualize what location and routing problems are. This kind of problems appear in many real situations and the aim of this paper is to explain the concept of cooperative agents for this kind of problems in order to implement it in future projects.

In goods delivery problems such as, for example, last mile parcel delivery, we have a set of demanding customers and another set of potential locations where to locate warehouses, intermediate warehouses, lockers or similar. In this scenario we are presented with two types of highly complex decisions to make. On the one hand, we must decide where to install these locations and how to allocate customers to these locations in a way that minimizes total cost. On the other hand, we must decide how to deal with our fleet at the end points (customers or storage lockers).

Agent Cooperation

The process starts with the arrival of goods at general warehouses. They are then usually shipped either directly to an end customer or to a smaller intermediate warehouse, but there are multiple situations where the process could be much more efficient through the cooperation of the agents involved. For example, in rural environments where instead of N people going to collect these goods, only one moves and collects both the goods destined for that agent and those destined for his neighbors. These cooperative agents bring the supplies closer to points that are more accessible to the rest of the neighbors who, for various reasons, do not have the possibility of traveling to the general stores to pick up the supplies. Also, when we place an order, we can choose to have it delivered to us at a distribution point where we must go to pick up the order.

Similarly, we can also cooperate when we talk about routes. It is common that not all deliveries are made by the same vehicle, either because it is too costly or because it cannot access all the points along the route. The ‘main’ vehicle deposits the cargo at intermediate distribution centers. Smaller vehicles, such as electric scooters, are then used to reduce emissions and reduce delivery time. But what could the transport company offer me to use my store or store as an intermediate depot? How much would they be willing to pay us?

Another model of cooperation is found when, instead of “forcing” the vehicles to visit all delivery points, they only visit part of them and the merchandise from the points not visited is left at one of the visited ones. Logically, the unvisited customers will have to move to one of the visited ones. But in exchange for what? A reduction in delivery costs? This type of collaboration also occurs, for example, in a shoe store where, if they do not have a specific size, they can order it from another store, without the need for the customer to go to the store where they have the shoe in question. Another possible example is in the case of a fire in which different fire stations cooperate to extinguish a fire located in a specific area of the city. In this case the “customer” would be the fire that remains fixed at one point, but is attended by several nearby fire stations.

How to establish a fair price for cooperative agents

It is important to determine the appropriate price to be paid to each cooperative agent. To determine the right amount we must take into account the effort that each cooperative agent has to make to pick up those orders for the rest of the customers or the savings for the carrier by depositing in intermediate lockers or the savings by not having to visit all the nodes. These savings need to be measured and shared with the cooperative agents.

Another decision to make, do we set a common price for all agents or do we pay a different price to each individual depending on the degree of cooperation? To determine these prices and savings, we can use Operations Research models and simulate the whole process under different cost, fleet, operational, strategy, etc. models. For example, there are several types of networks for the discussed case studies:

  • Median model: the cost is directly related to the total distance traveled (from the main warehouse to the cooperative agents and from the cooperative agents to the last customer).
  • Covering Model: The cost is fixed for all customers within the radius of action of each cooperative agent. This type of model seeks to maximize the covering demand of each agent.
  • Mixed Median-Covering: Combines the concepts of median and covering and certain customers will be served by the median model and the rest by the covering model.


Which approach or strategy do you think is better? Should we make decisions based on our intuition or based on data? At OGA we bet on the use of advanced analytics, the use of digital twins of complex logistic processes and powerful algorithms to obtain reliable results and simulations and make decisions based on this data.


Adding cooperative agents to our logistics process can be interesting and beneficial for all parties (carrier and end customers) as long as we are able to measure the total savings and share them.

Acerca del autor

Arturo López-Damas OGA
Arturo López-Damas
Optimization Consultant en OGA

Software Engineer in Information Systems by Pablo de Olavide University (UPO) with experience in Optimization, Data Analysis and Data Representation. Enthusiast of data-driven solutions with real applications.

I love music, new challenges and good food.