Optimization of Large-Scale Hydrogen Supply Chain Network Design Problem with Multi-period

Optimizing the hydrogen supply chain is pivotal for advancing hydrogen toward commercial viability. This paper introduces a mixed-integer nonlinear programming model to evaluate the cost and determine the optimal configuration of the supply chain. To address the challenge of running time on a large-scale computation, an algorithm combining a genetic algorithm and mixed integer linear programming is proposed. The algorithm is compared with the results obtained by the Cplex solver in an instance of France. The results highlight the performance of the hybrid algorithm and show the advantages of the model in terms of runtime.