Abstract
AbstractThe Conflict-Free Electric Vehicle Routing Problem (CF-EVRP) is a combinatorial optimization problem of designing routes for vehicles to execute tasks such that a cost function, typically the number of vehicles or the total travelled distance, is minimized. The CF-EVRP involves constraints such as time windows on the tasks’ execution, limited operating range of the vehicles, and limited capacity on the number of vehicles that a road segment can simultaneously accommodate. In previous work, the compositional algorithm ComSat was introduced to solve the CF-EVRP by breaking it down into sub-problems and iteratively solve them to build an overall solution. Though ComSat showed good performance in general, some problem instances took significant time to solve due to the high number of iterations required to find solutions for two sub-problems, namely the Routing Problem, and the Paths Changing Problem. This paper addresses the bottlenecks of ComSat and presents new formulations for both sub-problems in order to reduce the number of iterations required to find feasible solutions to the CF-EVRP. Experiments on sets of benchmark instances show the effectiveness of the presented improvements.
Funder
VINNOVA
EUREKA ITEA3 AIToC
Knut och Alice Wallenbergs Stiftelse
Chalmers AI Research Centre
Publisher
Springer Science and Business Media LLC
Subject
Electrical and Electronic Engineering,Modeling and Simulation,Control and Systems Engineering
Reference47 articles.
1. Abderrahim M, Bekrar A, Trentesaux D, Aissani N, Bouamrane K (2020) Manufacturing 4.0 operations scheduling with AGV battery management constraints. Energies 13(18):4948
2. Aloul FA, Al Rawi B, Aboelaze M (2006) Identifying the shortest path in large networks using boolean satisfiability. In: 2006 3rd international conference on electrical and electronics engineering, pp 1–4
3. Arumugam S, Brandstädt A, Nishizeki T, Thulasiraman K (2016) Handbook of Graph Theory, Combinatorial Optimization, and Algorithms, vol 34. CRC Press, New York
4. Barrett CW, Sebastiani R, Seshia SA, Tinelli C et al (2009) Satisfiability modulo theories. Handbook of Satisfiability 185:825–885
5. Bjørner N, Phan A-D, Fleckenstein L (2015) $$\nu $$Z-an optimizing SMT solver. In: International conference on tools and algorithms for the construction and analysis of systems, pp 194–199