Abstract
This paper introduces the Dynamic Multiperiod Vehicle Routing Problem with Probabilistic Information, an extension of the Dynamic Multiperiod Vehicle Routing Problem in which, at each time period, the set of customers requiring a service in later time periods is unknown, but its probability distribution is available. Requests for service must be satisfied within a given time window that comprises several time periods of the planning horizon. We propose an adaptive service policy that aims at estimating the best time period to serve each request within its associated time window in order to reduce distribution costs. The effectiveness of this policy is compared with that of two alternative basic policies through a series of computational experiments.
Original language | English |
---|---|
Pages (from-to) | 31-39 |
Number of pages | 9 |
Journal | Computers and Operations Research |
Volume | 48 |
DOIs | |
Publication status | Published - Aug 2014 |
Funding
The authors are very grateful to Claudia Archetti for providing us the code of the VNS heuristic used to find solutions to the daily subproblems, and to Min Wen who provided the data used in [19] . This work was partly supported by the Canadian Natural Sciences and Engineering Research Council under grant 39682-10 and by the Spanish Ministry of Economía y Competitividad through Grant MTM2012-36163-C06-05 . Thanks are due to a referee who provided several valuable comments.
Keywords
- Dynamic vehicle routing
- VNS
ASJC Scopus subject areas
- General Computer Science
- Modelling and Simulation
- Management Science and Operations Research