Conference Proceedings

Fuzzy C-Means-based Scenario Bundling for Stochastic Service Network Design

Xiaoping Jiang, Ruibin Bai, Dario Landa-Silva, Uwe Aickelin

2017 IEEE Symposium Series on Computational Intelligence (SSCI) | IEEE Xplore | Published : 2017

Abstract

Stochastic service network designs with uncertain demand represented by a set of scenarios can be modelled as a large-scale two-stage stochastic mixed-integer program (SMIP). The progressive hedging algorithm (PHA) is a decomposition method for solving the resulting SMIP. The computational performance of the PHA can be greatly enhanced by decomposing according to scenario bundles instead of individual scenarios. At the heart of bundle-based decomposition is the method for grouping the scenarios into bundles. In this paper, we present a fuzzy c-means-based scenario bundling method to address this problem. Rather than full membership of a bundle, which is typically the case in existing scenari..

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University of Melbourne Researchers

Grants

Awarded by National Natural Science Foundation of China


Awarded by Zhejiang Natural Science Foundation


Awarded by Ningbo Science and Technology Bureau


Funding Acknowledgements

This work is funded by the National Natural Science Foundation of China [grant number NSFC 71471092]; Zhejiang Natural Science Foundation [grant number LR17G010001]; Ningbo Science and Technology Bureau [grant number 2011B81006], [grant number 2014A35006]. We also greatly acknowledge the support from the International Doctoral Innovation Centre (IDIC) scholarship scheme.