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This study extends the fueling station location problem to consider interdependencies with fuel delivery. Specifically, we present a new variant of the bi-objective capacitated location routing problem (bi-objective CLRP), flow capturing location problem with fuel delivery (FCLP-FD), to simultaneously determine the location of hydrogen fueling stations (HFSs) and routing decisions for hydrogen delivery trucks. The FCLP-FD is proposed to overcome barriers to the deployment of HFSs. The HFS network is determined while maximizing the fueling demand flow captured and minimizing the total daily cost. The metaheuristic algorithm of adaptive large neighborhood search (ALNS) was developed, and its performance on solving bi-objective optimization problems was tested and compared with the genetic algorithm (GA). The developed model and algorithms were applied to a case study in Bourgogne-Franche-Comte, France. Results show that the model improved the understanding of decision-makers about various components within the HFS network and provides useful managerial insights regarding the role of fleet composition and physical forms of hydrogen. In terms of algorithm performance, the GA was faster than ALNS for all the tested instances; however, ALNS is characterized by a better average gap, which is the differences between the obtained Pareto front (generated by ALNS) and the optimal one (generated using IBM ILOG CPLEX Optimization Studio). |
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