Multi-Compartment Fuel Truck Routing

Product Used: Route Optimization API

Background

Consider a fuel distributor operating a fleet of tanker trucks supplying fuel to 8 gas stations across a large city. Each station requires different quantities and types of fuel. At the same time, the distributor operates 2 tanker trucks with multiple compartments of fixed sizes. Before starting deliveries, each compartment must be filled with a specific fuel type, and once assigned, that compartment can only deliver that fuel during the trip. Since different delivery scenarios require different fuel mixes, choosing the wrong compartment configuration can lead to unused capacity, additional trips, or inefficient routing plans.

Problem Statements

When multiple fuel types can be loaded into a compartment of tanker trucks, the fuel distributors face following challenges:

Multiple compartment loading configurations

Determining the best capacity configuration before trucks leave the depot is critical. For example, a truck with three compartments - 5,000 liters, 4,000 liters and 3,000 liters - may be loaded in several ways:

The optimal configuration depends on the mix of fuel orders that must be delivered on a particular day. If the routing system assumes a fixed capacity configuration for every truck, it may fail to utilize compartments effectively or it may suggest additional trucks to fulfill the same set of orders.

Compartment-to-Order Matching Complexity

Dispatchers face the complex task of ensuring available capacity across compartments can satisfy the demand so that they can batch & match orders to compatible trucks and load each truck's compartments with required fuel type before attempting to find efficient routes.

Without an advanced routing system which can intelligently match orders to efficient loading configurations, orders may remain unassigned even though fleet capacity exists and planning routes becomes complex and time-consuming.

Solution

NextBilion.ai Route Optimization API supports alternative capacity configurations for vehicles allowing the optimizer to evaluate multiple possible compartment setups and choose the most suitable one for the given delivery scenario.

Leverage alternative capacity

The API allows users to define all possible loading configurations for a truck - one primary and several alternatives, representing different ways the compartments of a truck can be loaded with fuel types:

1
"capacity": [5000,4000,3000],
2
"alternative_capacities": [
3
            [5000,3000,4000],
4
            [4000,5000,3000],
5
            [4000,3000,5000],
6
            [3000,5000,4000],
7
            [3000,4000,5000]
8
           ]

Optimize for best capacity configuration

When multiple trucks and delivery orders are involved, the optimizer evaluates the available capacity configurations across the fleet. For each truck, it determines the loading configuration which best satisfies the combination of fuel types required to fulfil orders and then it automatically generates feasible and efficient routing plans for multi-compartment fuel fleets.

Sample Request and Response

Following is a JSON request that we built for this case and the corresponding response.

API Request

1
curl --location 'https://api.nextbillion.io/optimization/v2?key=<your_api_key>' --header 'Content-Type: application/json' --data '{...}'

API Response

1
{
2
  "description": "Multi-Compartment Fuel Trucks",
3
  "result": '{...}',
4
  "status": "Ok",
5
  "message": ""

We observed how the optimizer evaluated and leveraged alternative capacity configurations for vehicles instead of merely going with the primary-capacity configuration of the vehicle. It dynamically considered various allowed compartment capacity configurations for each vehicle to identify and select the most suitable configuration that maximized efficiency for the given scenario resulting in reducing the number of total trips, minimizing mileage, and ensuring that each vehicle deployment is optimized.