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Reliable hub-and-spoke systems with multiple capacity levels and flow dependent discount factor

Azizi, Nader, Salhi, Said (2022) Reliable hub-and-spoke systems with multiple capacity levels and flow dependent discount factor. European Journal of Operational Research, 298 (3). pp. 834-854. ISSN 0377-2217. (doi:10.1016/j.ejor.2021.07.041) (KAR id:90136)

Abstract

In this paper we investigate the reliable single allocation p-hub location problem with multiple capacity levels and flow dependent discount factor. We first present new and novel MIP formulations that are built upon the well-known uncapacitated FLOWLOC model proposed by O'Kelly and Bryan (1998). The proposed reliable models aim at simultaneously determining (a) the optimal location of the hubs, (b) the allocation of demand to these hubs,(c) the backup facilities for each demand point, (d) the hub capacity level to handle the normal flow, (e) the additional capacity to handle excessive rerouted flows due to possible hub disruption, (f) the values of discount factor for inter-hub links at normal and (g) the discount factor to be applied on inter-hub links should volume of flow increases because of hub disruption. The proposed mathematical models could solve small instances to optimality using a commercial optimiser such as CPLEX. To solve large instances we propose a variant of the VNS algorithm, namely, the reduced VNS. We present computational results including lower and upper bounds of the optimal solutions to problems with 15, 20 and 25 nodes and the upper bounds of the solutions to larger problems up to 170 nodes. Managerial insights for the reliable hub location problem with and without the use of flow dependent discount factors are presented and recommendations on the use of trade-off curves between the two objectives of minimizing the network cost in normal and disrupted conditions are also provided.

Item Type: Article
DOI/Identification number: 10.1016/j.ejor.2021.07.041
Uncontrolled keywords: Location
Subjects: H Social Sciences
Divisions: Divisions > Kent Business School - Division > Department of Analytics, Operations and Systems
Depositing User: Said Salhi
Date Deposited: 10 Sep 2021 13:03 UTC
Last Modified: 05 Nov 2024 12:55 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/90136 (The current URI for this page, for reference purposes)

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