Stochastic local search procedures for the probabilistic two-day vehicle routing problem

Doerner, Karl F. and Gutjahr, Walter J. and Hartl, Richard F. and Lulli, Guglielmo (2008) Stochastic local search procedures for the probabilistic two-day vehicle routing problem. In: Advances in Computational Intelligence in Transport, Logistics, and Supply Chain Management. Studies in Computational Intelligence . Springer, pp. 153-168. ISBN 9783540690245

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Abstract

This chapter is motivated by the study of a real-world application on blood delivery. The Austrian Red Cross (ARC), a non-profit organization, is in charge of delivering blood to hospitals on their request. To reduce their operating costs through higher flexibility, the ARC is interested in changing the policy of delivering blood products. Therefore it wants to provide two different types of service: an urgent service which delivers the blood within one day and the other, regular service, within two days. Obviously the two services come at different prices. We formalize this problem as a stochastic problem, with the objective to minimize the average long-run delivery costs, knowing the probabilities governing the requests of service. To solve real instances of our problem in a reasonable time, we propose three heuristic procedures whose core routine is an Ant Colony Optimization (ACO) algorithm, which differ from each other by the rule implemented to select the regular blood orders to serve immediately. We compare the three heuristics on both a set of real-world data and on a set of randomly generated synthetic data. Computational results show the viability of our approach.

Item Type: Contribution in Book/Report/Proceedings
Uncontrolled Keywords: /dk/atira/pure/subjectarea/asjc/1700/1702
Subjects:
Departments: Lancaster University Management School > Management Science
ID Code: 128792
Deposited By: ep_importer_pure
Deposited On: 05 Nov 2018 13:20
Refereed?: No
Published?: Published
Last Modified: 01 Jan 2020 10:52
URI: https://eprints.lancs.ac.uk/id/eprint/128792

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