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

Fatima Zahraa Grine, Oulaid Kamach, Abdelhakim Khatab, Naoufal Sefiani


The present paper deals with a variant of hub location problems (HLP): the un- capacitated single allocation p-hub median problem (USApHMP). This problem consists to jointly locate hub facilities and to allocate demand nodes to these se-lected 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 articial immune systems (AIS) framework, this paper de-velops a new approach to effciently 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 con-ducted 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 out perform the best-known solutions in the literature.


artificial immune system; clonal selection algorithm; evolutionary computations; hub location problem; metaheuristic; p-hub median problem;

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ISSN 2088-8708, e-ISSN 2722-2578