Title: Optimisation of dynamic hydrogen supply chain network: a mathematical programming approach

Authors: Jafar Razmi; Reza Babazadeh; Mohamad Amin Kaviani

Addresses: School of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran ' Faculty of Engineering, Urmia University, Urmia, West Azerbaijan Province, Iran ' Young Researchers and Elite Club, Shiraz Branch, Islamic Azad University, Shiraz, Iran

Abstract: The recent studies on hydrogen supply chain (HSC) explicitly state that optimising the HSC flows is one of the main elements leads to have an efficient hydrogen supply network and plays a vital role in total costs minimisation of hydrogen production and transportation. Considering the importance of this issue, this study presents a mathematical programming optimisation model to help the HSC managers make robust strategic and tactical decisions related to HSC management. Generally, the HSC echelons include gathering raw material centres, production facilities and hydrogen distribution and storage centres. The proposed approach introduces a mix-integer linear programming (MILP) model optimising the HSC network at the strategic level of decision-making through minimising both capital and operational costs of the HSC. Furthermore, sensitivity analysis is accomplished on the transportation cost of materials within the HSC network which constitutes the major share of total costs. Moreover, a numerical example is performed to demonstrate the efficiency and validity of the proposed optimisation model. The obtained results confirm the capability of the presented model for HSC network optimisation. The main finding of the research indicated that hydrogen transportation cost is completely sensitive to HSC network structure.

Keywords: supply chain network design; hydrogen supply chain; mathematical modelling; optimisation; supply chain management; mixed-integer linear programming.

DOI: 10.1504/IJAMS.2018.093801

International Journal of Applied Management Science, 2018 Vol.10 No.3, pp.192 - 216

Received: 28 Dec 2016
Accepted: 09 Aug 2017
Published online: 06 Aug 2018 *

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