Title: Hybrid transportation model forecasting and optimisation with practical fuel supply chain

Authors: Nasser M. Ayoub; Hossam A. Gabbar

Addresses: Production Technology Department, Faculty of Industrial Education, Helwan University, El Sawah St., In Front Of Bisco Misr, El Amireya, Cairo, Egypt ' Faculty of Energy Systems and Nuclear Science, University of Ontario Institute of Technology, 2000 Simcoe St. N., Oshawa, L1H 7K4 ON, Canada

Abstract: This research proposes an integrated application model for hybrid transportation system (HTS) that include environmentally sustainable vehicles, such as EVs and hydrogen vehicles as main ingredients. A medium- to long-term market forecasting was performed using autoregressive integrated moving average (ARIMA) model to identify the transportation mix by the year 2030. A fuel supply chain model developed as mixed-integer linear programming model, and solved using GA methods. A case study on three future scenarios for HTS in year 2030 was presented to check, vehicles use CO₂ emissions, costs, NG demands, the numbers of fuel distribution centres (FDCs) and NG storage facilities. In the investigated scenarios, the vehicles use was reduced from 97% in 2009 to 81.5%, 72% and 63% respectively. The CO₂ emissions were reduced by about 12%. The cost of smearing the second and third scenarios was found to be 19.25 M.USD and 36.79 M.USD more than the reference scenario.

Keywords: hybrid transport systems; HST; infrastructure modelling; smart grid; fuel production; fuel supply chains; forecasting; optimisation; supply chain management; SCM; ARIMA; electric vehicles; hydrogen vehicles; transport mix; supply chain modelling; mixed-integer linear programming; MILP; genetic algorithms; CO2; carbon dioxide; carbon emissions; natural gas; fuel distribution centres.

DOI: 10.1504/IJSCOR.2015.072617

International Journal of Supply Chain and Operations Resilience, 2015 Vol.1 No.3, pp.243 - 279

Received: 16 Jul 2014
Accepted: 23 Jan 2015
Published online: 22 Oct 2015 *

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