An SMT Based Compositional Algorithm to Solve a Conflict-Free Electric Vehicle Routing Problem
Paper in proceeding, 2021

The Vehicle Routing Problem (VRP) is the combinatorial optimization problem of designing routes for vehicles to visit customers in such a fashion that a cost function, typically the number of vehicles, or the total travelled distance is minimized. The problem finds applications in industrial scenarios, for example where Automated Guided Vehicles run through the plant to deliver components from the warehouse. This specific problem, henceforth called the Electric Conflict-Free Vehicle Routing Problem (CF-EVRP), involves constraints such as limited operating range of the vehicles, time windows on the delivery to the customers, and limited capacity on the number of vehicles the road segments can accommodate at the same time. Such a complex system results in a large model that cannot easily be solved to optimality in reasonable time. We therefore developed a compositional algorithm that breaks down the problem into smaller and simpler sub-problems and provides sub-optimal, feasible solutions to the original problem. The algorithm exploits the strengths of SMT solvers, which proved in our previous work to be an efficient approach to deal with scheduling problems. Compared to a monolithic model for the CF-EVRP, written in the SMT standard language and solved using a state-of-the-art SMT solver the compositional algorithm was found to be significantly faster.

Routing

Vehicle routing

Roads

Conferences

Job shop scheduling

Electric vehicles

Computer aided software engineering

Author

Sabino Francesco Roselli

Chalmers, Electrical Engineering, Systems and control

Martin Fabian

Chalmers, Electrical Engineering, Systems and control

Knut Åkesson

Chalmers, Electrical Engineering, Systems and control

IEEE International Conference on Automation Science and Engineering

21618070 (ISSN) 21618089 (eISSN)

Vol. 2021-August 1364-1369
9781665418737 (ISBN)

17th IEEE International Conference on Automation Science and Engineering, CASE 2021
Lyon, France,

Subject Categories

Computational Mathematics

Control Engineering

Computer Science

DOI

10.1109/CASE49439.2021.9551521

More information

Latest update

11/2/2021