@article{ref1,
title="A hybrid method for transportation with stochastic demand",
journal="International journal of logistics research and applications",
year="2015",
author="Corso, Leandro L. and Wallace, Mark",
volume="18",
number="4",
pages="342-354",
abstract="In industrial transportation, the forecast demand at each destination may be affected by a number of factors. Consequently, a conventional transport plan often fails to match the reality, and the planned transport capacity is either insufficient to meet the demand or wastefully excessive. In this paper, we introduce a new algorithm to generate a minimal cost transport plan that meets a given level of reliability. The reliability of a candidate solution is measured through simulating each candidate solution against a large number of scenarios. To search for reliable solutions, a genetic algorithm method is applied as an external loop. The minimal transport cost is achieved through a deterministic optimisation algorithm. We show that this problem decomposition in principle enables the optimal solution of the original non-deterministic problem to be found. Experimental results establish the practical usefulness of the proposed algorithm.<p /> <p>Language: en</p>",
language="en",
issn="1367-5567",
doi="10.1080/13675567.2015.1010494",
url="http://dx.doi.org/10.1080/13675567.2015.1010494"
}