Optimization of a hydrogen supply chain network design under demand uncertainty by multi-objective genetic algorithms

•This paper addresses the multi-objective design of a hydrogen supply chais under demand uncertainty.•The potential of genetic algorithms is explored to cope with the multi-objective formulation.•Better compromise solutions are produced than those obtained with ε-constraint MILP approach.•Demand unc...

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Bibliographic Details
Published in:	Computers & chemical engineering Vol. 140; p. 106853
Main Authors:	Robles, Jesus Ochoa, Azzaro-Pantel, Catherine, Aguilar-Lasserre, Alberto
Format:	Journal Article
Language:	English
Published:	Elsevier Ltd 02.09.2020 Elsevier
Subjects:	Chemical and Process Engineering Engineering Sciences Fuzzy techniques Genetic algorithm Hydrogen supply chain Multiobjective optimization TOPSIS SCND GWP NSGA-II Hydrogen supply chain MILP GHG Fuzzy techniques MINLP CCS TDC Genetic algorithm Multiobjective optimization HSC SMR GA MCDM TOPSIS
ISSN:	0098-1354, 1873-4375
Online Access:	Get full text
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