Journal
26TH EUROPEAN SYMPOSIUM ON COMPUTER AIDED PROCESS ENGINEERING (ESCAPE), PT A
Volume 38A, Issue -, Pages 805-810Publisher
ELSEVIER SCIENCE BV
DOI: 10.1016/B978-0-444-63428-3.50139-9
Keywords
Hydrogen Supply Chain; Optimization; Genetic Algorithm; NSGA II
Ask authors/readers for more resources
Nowadays, hydrogen is considered as one of the most promising energy carriers for mobility applications. A model of the hydrogen supply chain (HSC) based on MILP formulation (Mixed Integer Linear Programming) in a multi-objective formulation implemented via the epsilon-constraint method to generate the Pareto front was carried out in a previous work and applied to the region of Midi-Pyrenees. Yet, the size and in particular the number of binary variables often may lead to difficulties for problem solution. In this work, the potential of genetic algorithms (GA) via a variant of NSGA-II is explored to cope with the multi-objective formulation, in order to produce compromise solutions automatically. The results obtained by using GA are compared to those presented in the base model as well as the computational effort to generate the solutions. The solutions obtained by GA exhibit the same order of magnitude as those obtained with MILP in the mono-criterion problem, and some compromise solutions are produced in the multi-objective formulation.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available