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TO Capacitated Transportation Optimization

In this example, we will learn how to find routes for serving customers considering demand values and vehicle capacities with the help of the Capacitated Transportation Optimization experiment.

Note that in the anyLogistix PLE, the actual scenario data can differ from this description.

Problem definition

We consider a supply chain with two warehouses (located in Alīgarh and Navi Airoli), which supply 35 customers (20 in PLE version) in India with tea. Demand is historical: exact number of products is delivered to customers on a specific date. The truck capacity is 50 m3

The truck will be able to fetch orders for several destination points, which will be visited following the specified index. It will reduce costs.

We would like to meet the following requirements:

  • 5 shipments in September
  • The Maximum distance between objects - 1800 km
  • The Maximum length of the returning segment - 2000 km
Goal

Аorm a sequence of destination points (customers) that will be served in a certain order considering:

  • Locations of sites and customers
  • Paths between them
  • Demand of the customers
  • Capacity of the vehicle type used to deliver products
Result

The result of the experiment offers a delivery schedule with optimal routes. The data on the generated paths, transportation costs, traveled distance is shown in the corresponding tables.

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