English

Asynchronous Cooperative Optimization of a Capacitated Vehicle Routing Problem Solution

Distributed, Parallel, and Cluster Computing 2025-11-26 v1 Discrete Mathematics

Abstract

We propose a parallel shared-memory schema to cooperatively optimize the solution of a Capacitated Vehicle Routing Problem instance with minimal synchronization effort and without the need for an explicit decomposition. To this end, we design FILO2x^x as a single-trajectory parallel adaptation of the FILO2 algorithm originally proposed for extremely large-scale instances and described in Accorsi and Vigo (2024). Using the locality of the FILO2 optimization applications, in FILO2x^x several possibly unrelated solution areas are concurrently asynchronously optimized. The overall search trajectory emerges as an iteration-based parallelism obtained by the simultaneous optimization of the same underlying solution performed by several solvers. Despite the high efficiency exhibited by the single-threaded FILO2 algorithm, the computational results show that, by better exploiting the available computing resources, FILO2x^x can greatly enhance the resolution time compared to the original approach, still maintaining a similar final solution quality for instances ranging from hundreds to hundreds of thousands customers.

Keywords

Cite

@article{arxiv.2511.19445,
  title  = {Asynchronous Cooperative Optimization of a Capacitated Vehicle Routing Problem Solution},
  author = {Luca Accorsi and Demetrio Laganà and Federico Michelotto and Roberto Musmanno and Daniele Vigo},
  journal= {arXiv preprint arXiv:2511.19445},
  year   = {2025}
}
R2 v1 2026-07-01T07:52:44.960Z