An adaptive guidance meta-heuristic for the vehicle routing problem with splits and clustered backhauls

An adaptive guidance meta-heuristic for the vehicle routing problem with splits and clustered backhauls

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Article ID: iaor201526774
Volume: 66
Issue: 7
Start Page Number: 1222
End Page Number: 1235
Publication Date: Jul 2015
Journal: Journal of the Operational Research Society
Authors: , , ,
Keywords: combinatorial optimization, programming: integer, programming: linear
Abstract:

This paper presents the case study of an Italian carrier, Grendi Trasporti Marittimi, which provides freight transportation services by trucks and containers. Its trucks deliver container loads from a port to import customers and collect container loads from export customers to the same port. In this case study, all import customers in a route must be serviced before all export customers, each customer can be visited more than once and containers are never unloaded or reloaded from the truck chassis along any route. We model the problem using an Integer Linear Programming formulation and propose an Adaptive Guidance metaheuristic. Our extensive computational experiments show that the adaptive guidance algorithm is capable of determining good‐quality solutions in many instances of practical or potential interest for the carrier within 10min of computing time, whereas the mathematical formulation often fails to provide the first feasible solution within 3h of computing time.

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