TY - GEN
T1 - Efficient Mixed Integer Programming Formulation for the Uncapacitated r-Allocation p-Hub Center Problem
AU - Jovanovic, Raka
AU - Urošević, Dragan
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.
PY - 2025/7/12
Y1 - 2025/7/12
N2 - This paper addresses the uncapacitated r-allocation p-hub center problem (UrApHCP), which is essential in hub location modeling for transportation and telecommunications systems. The study enhances the computational efficiency of Mixed Integer Programming (MIP) formulations for UrApHCP, which often struggle with multiple equivalent solutions. The proposed method extends the traditional objective function by including overall transport cost along with the maximal minimal transportation cost, using a lexicographic objective function. This extension is applied to two MIP formulations, the four-index model (FIM) and the flow-based model (FBM), to better distinguish solutions and improve efficiency. Computational experiments on standard benchmark instances show that the extended models significantly reduce computational time, highlighting their practical advantages. This research advances optimization techniques for complex hub location problems by improving the computational efficiency of MIP formulations.
AB - This paper addresses the uncapacitated r-allocation p-hub center problem (UrApHCP), which is essential in hub location modeling for transportation and telecommunications systems. The study enhances the computational efficiency of Mixed Integer Programming (MIP) formulations for UrApHCP, which often struggle with multiple equivalent solutions. The proposed method extends the traditional objective function by including overall transport cost along with the maximal minimal transportation cost, using a lexicographic objective function. This extension is applied to two MIP formulations, the four-index model (FIM) and the flow-based model (FBM), to better distinguish solutions and improve efficiency. Computational experiments on standard benchmark instances show that the extended models significantly reduce computational time, highlighting their practical advantages. This research advances optimization techniques for complex hub location problems by improving the computational efficiency of MIP formulations.
KW - Hub location problem
KW - Mixed integer programming
KW - p-hub
UR - https://www.scopus.com/pages/publications/105011264113
U2 - 10.1007/978-981-96-5223-5_23
DO - 10.1007/978-981-96-5223-5_23
M3 - Conference contribution
AN - SCOPUS:105011264113
SN - 9789819652228
T3 - Lecture Notes in Networks and Systems
SP - 277
EP - 289
BT - Innovations in Communication Networks
A2 - Bhateja, Vikrant
A2 - Abdul Hameed, Vazeerudeen
A2 - Udgata, Siba K.
A2 - Azar, Ahmad Taher
PB - Springer Science and Business Media Deutschland GmbH
T2 - 5th International Conference on Data Engineering and Communication Technology, ICDECT 2024
Y2 - 28 September 2024 through 29 September 2024
ER -