Uncertain Programming Models for Sustainable Hub Covering Location Problem Over Incomplete Network

Hub covering location problem focuses on the construction of the hub network. The importance of this problem has been addressed in many fields including freight transportation and telecommunication network. As a long-term strategic decision problem, the construction of the hub network has large scale environmental influences especially the emissions of greenhouse gas. In the meanwhile, the precise information of the parameters cannot be obtained. Therefore, this work investigates the sustainable hub covering location problem with uncertain parameters. The purpose is to minimize the overall cost and impose restrictions on the total CO₂ emissions, simultaneously. The travel times are depicted by uncertain variables to portray inherent indeterminacy within this problem. The incomplete network is adopted to decrease the total investment cost considerably. Accordingly, two uncertain programming models are constructed and transformed into their equivalent forms. A modified genetic algorithm is proposed to solve the proposed models. Several experiments are performed to interpret the efficiency of the proposed algorithm and the validity of the proposed models. The experimental results show that accounting for the emission restriction and the adoption of incomplete hub network will significantly affect the overall investment cost and the construction of the hub network.