Title: A stochastic programming model for hub-and-spoke network with uncertain flows

Authors: Qing-Mi Hu; Zhi-Hua Hu

Addresses: Logistics Research Center, Shanghai Maritime University, Shanghai 201306, China ' Logistics Research Center, Shanghai Maritime University, Shanghai 201306, China; School of Economics and Management, Tongji University, Shanghai 200092, China

Abstract: Hub-and-spoke network (HSN) exploits economy of scale in transportation and reduces logistics operational cost through collaborations among nodes. Because of the uncertainty of origin-destination (OD) flows between nodes, the uncertainty increases the risk of selecting capacities for nodes and affects the analysis of contribution of the nodes to the HSN. First, considering the characteristics of the uncertainty of OD flows, the throughput capacities of spoke nodes are determined based on stochastic programming approach and expectation theory; then, a stochastic mixed-integer linear programming model for designing hub-and-spoke network is established based on the capacities of spokes, and the structure of the HSN and throughput capacities of the hubs are designed. Second, the classification method of nodes is formulated based on the transportation flows between spokes, resource utilisation degree, and the branch and trunk convective equilibrium degree. A multi-attribute utility evaluation function for evaluating contribution rates of nodes to the HSN is established based on the proposed evaluation indices. Finally, the existing problems about network operational and adjustment strategies are analysed based on the contribution rates of the nodes to the HSN.

Keywords: logistics; hub-and-spoke networks; HSN; uncertain flows; capacity design; multi-attribute utility evaluation; stochastic programming; uncertainty; throughput capacity; expectation theory; mixed-integer linear programming; MILP; network design; spoke capacity; transport flows; resource utilisation; branch and trunk convective equilibrium.

DOI: 10.1504/IJISE.2015.072268

International Journal of Industrial and Systems Engineering, 2015 Vol.21 No.3, pp.302 - 319

Received: 01 Oct 2013
Accepted: 02 Mar 2014
Published online: 08 Oct 2015 *

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