Effects of Disruption Risks on Biorefinery Location Design

Yun Bai, Xiaopeng Li, Fan Peng, Xin Wang and Yanfeng Ouyang
Additional contact information
Yun Bai: Center for Advanced Infrastructure and Transportation, Rutgers, the State University of New Jersey, 100 Brett Road, Piscataway, NJ 08854-8058, USA
Xiaopeng Li: Department of Civil and Environmental Engineering, Mississippi State University, 235L Walker Engineering Building, Starkville, MS 39762-9546, USA
Fan Peng: Operations Research Department, CSX Transportation, Inc., Jacksonville, FL 32202, USA
Xin Wang: Department of Civil and Environmental Engineering, University of Illinois at Urbana-Champaign, 205 N. Mathews Ave., Urbana, IL 61801, USA
Yanfeng Ouyang: Department of Civil and Environmental Engineering, University of Illinois at Urbana-Champaign, 205 N. Mathews Ave., Urbana, IL 61801, USA

Energies, 2015, vol. 8, issue 2, 1-19

Abstract: While ever-growing bio-ethanol production poses considerable challenges to the bioenergy supply chain, the risk of refinery operation disruptions further compromises the efficiency and reliability of the energy supply system. This paper applies discrete and continuous reliable facility location models to the design of reliable bio-ethanol supply chains so that the system can hedge against potential operational disruptions. The discrete model is shown to be suitable for obtaining the exact optimality for small or moderate instances, while the continuous model has superior computational tractability for large-scale applications. The impacts of both site-independent and dependent disruptions ( i.e. , due to flooding) are analyzed in empirical case study for the State of Illinois (one of the main biomass supply states in the U.S.). The reliable solution is compared with a deterministic solution under the same setting. It is found that refinery disruptions, especially those site-dependent ones, affect both optimal refinery deployment and the supply chain cost. Sensitivity analysis is also conducted to show how refinery failure probability and fixed cost (for building biorefineries) affect optimal supply chain configuration and the total expected system cost.

Keywords: biorefinery location; disruption uncertainty; reliable bio-ethanol supply chain network; biomass transportation; discrete facility location model; continuous approximation; Illinois bio-ethanol industry (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2015
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (18)

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