A new efficient metaheuristic for solving the Uncapacitated Single Allocation p-Hub Median Problem

Grine, Fatima Zahraa; Kamach, Oulaïd; Sefiani, Naoufal

doi:10.1109/logistiqua.2018.8428297

Cited by 4 publications

(1 citation statement)

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“…This paper is an extension to the work presented in [24]. In our previous work we provided a summary about theoretical framework of the artificial immune systems and a detailed review of the clonal selection algorithm.…”

Section: Introductionmentioning

confidence: 99%

An artificial immune system algorithm for solving the uncapacitated single allocation p-Hub median problem

Grine¹,

Kamach²,

Khatab

et al. 2021

IJECE

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The present paper deals with a variant of hub location problems (HLP): the uncapacitated single allocation p-Hub median problem (USApHMP). This problem consists to jointly locate hub facilities and to allocate demand nodes to these selected facilities. The objective function is to minimize the routing of demands between any origin and destination pair of nodes. This problem is known to be NP-hard. Based on the artificial immune systems (AIS) framework, this paper develops a new approach to efficiently solve the USApHMP. The proposed approach is in the form of a clonal selection algorithm (CSA) that uses appropriate encoding schemes of solutions and maintains their feasibility. Comprehensive experiments and comparison of the proposed approach with other existing heuristics are conducted on benchmark from civil aeronautics board, Australian post, PlanetLab and Urand data sets. The results obtained allow to demonstrate the validity and the effectiveness of our approach. In terms of solution quality, the results obtained outperform the best-known solutions in the literature.

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Section: Introductionmentioning

confidence: 99%