Cooperative receding horizon strategies for the multivehicle routing problem

Antonio Pietrabissa, Alessandro Di Giorgio, Guido Oddi, Giorgia Chini, Ming Li Chiang, Cecilia Poli

Research output: Contribution to journalArticlepeer-review


This paper deals with the dynamic Euclidean Multivehicle Routing Problem (MVRP) in both deterministic and uncertain scenarios. The objective of MVRP is to find the best paths for a fleet of vehicles that are cooperative to visit a set of targets. Based on the cooperative receding horizon (CRH) approach proposed in some previous works, which is vehicle-oriented, in this paper, we consider a target-oriented CRH, named tCRH, and then we propose a switching scheme, named sCRH, which is able to dynamically adjust the vehicle behaviors according to the time-varying configuration of both vehicles and targets, as well as to handle the situation with the appearance of unknown targets. The proposed sCRH counteracts the oscillation problem of CRH and improves the overall routing performances by adopting the advantages of both CRH and tCRH approach. Convergence results and simulation results are provided to validate the proposed approach.

Original languageEnglish
Pages (from-to)248-262
Number of pages15
JournalOptimal Control Applications and Methods
Issue number1
Publication statusPublished - Jan 1 2018
Externally publishedYes


  • cooperative control
  • multivehicle routing
  • receding horizon control

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Software
  • Control and Optimization
  • Applied Mathematics


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