A Hybrid Genetic - GRASP Algorithm for
the vehicle routing problem
Yannis
Marinakis1, Athanasios Migdalas1,
Panos M. Pardalos2 and Magdalene Marinakis3
1Decision
Support Systems Laboratory
Department of Production Engineering and Management
73100
2Department
of Industrial and Systems Engineering
3Industrial
Systems and Control Laboratory
Department of Production Engineering and Management
73100
e-mails: marinakis@ergasya.tuc.gr, sakis@verenike.ergasya.tuc.gr, pardalos@cao.ise.ufl.edu,
The
distribution of commodities, known by the generic name vehicle routing problem,
is one of the most important components of supply chain. The vehicle routing
problem, which is a hard combinatorial problem, has therefore attracted
considerable research attention and a number of algorithms have been proposed
for its solution. Hybridization techniques are very effective for the solution
of combinatorial optimization problems. This paper presents a genetic algorithm
based on Expanding Neighborhood Search technique proposed by Marinakis et al. for the solution of the vehicle routing
problem. The algorithm was tested on two different sets of benchmark problems:
the 14 benchmark problems proposed by Christofides
and the 20 large scale vehicle routing problems proposed by Golden.