Details

Autor(en) / Beteiligte

• Guimarans, D
• Herrero, R
• Riera, D
• Juan Pérez, Angel Alejandro
• Ramos, J

Titel

Combining constraint programming, lagrangean relaxation and probabilistic algorithms to solve the vehicle routing problem

Erscheinungsjahr

2011

Link zum Volltext

Quelle

SpringerLink (Online service)

Beschreibungen/Notizen

• This paper presents an original hybrid approach to solve the Capacitated Vehicle Routing Problem (CVRP). The approach combines a Probabilistic Algorithm with Constraint Programming (CP) and Lagrangian Relaxation (LR). After introducing the CVRP and reviewing the existing literature on the topic, the paper proposes an approach based on a probabilistic Variable Neighbourhood Search (VNS) algorithm. Given a CVRP instance, this algorithm uses a randomized version of the classical Clarke and Wright Savings constructive heuristic to generate a starting solution. This starting solution is then improved through a local search process which combines: (a) LR to optimise each individual route, and (b) CP to quickly verify the feasibility of new proposed solutions. The efficiency of our approach is analysed after testing some well-known CVRP benchmarks. Benefits of our hybrid approach over already existing approaches are also discussed. In particular, the potential flexibility of our methodology is highlighted. Peer Reviewed