Faster rollout search for the vehicle routing problem with stochastic demands and restocking

Luca Bertazzi and Nicola Secomandi

European Journal of Operational Research, 2018, vol. 270, issue 2, 487-497

Abstract: Rollout algorithms lead to effective heuristics for the single vehicle routing problem with stochastic demands (VRPSD), a prototypical model of logistics under uncertainty. However, they can be computationally intensive. To reduce their run time, we introduce a novel approach to approximate the expected cost of a route when executing any rollout algorithm for VRPSD with restocking. With a sufficiently large number of customers its theoretical speed-up factor is of big-o order 1/3. On a set of instances from the literature, our proposed technique applied to a known rollout algorithm and three variants thereof achieves speed-up factors that range from 0.26 to 0.34 when there are more than fifty customers, degrading only marginally the quality of the resulting routes. Our method also applies to the a priori case, in which case it is exact.

Keywords: Routing; Rollout algorithms; Restocking; Stochastic vehicle routing problem (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (8)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ejores:v:270:y:2018:i:2:p:487-497

DOI: 10.1016/j.ejor.2018.03.034

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