Stochastic optimization of sustainable industrial symbiosis based hybrid generation bioethanol supply chains

This paper studies new industrial symbiosis based hybrid generation bioethanol supply chain (ISHGBSC).A mathematical model is developed to design the ISHGBSC that is both robust and sustainable.The impact of various sustainability regulations on the design of ISHGBSC is examined.Results provide guidelines for policy makers to select appropriate sustainability regulations.Results provide guidelines for investors to develop sustainable strategies. Bioethanol has been considered as an important type of renewable energy that can help reduce energy crisis and environmental degradation. Under economic, technology, and sustainability consideration, food based 1st generation bioethanol and lignocellulosic-based 2nd generation bioethanol have to exist simultaneously. Therefore, it is necessary to design a hybrid generation bioethanol supply chain (HGBSC) to sustainably meet the ever-increasing energy demand and different government-mandated sustainability standards related to green sustainability such as greenhouse gas (GHG) emissions, irrigation land and water usage, and energy efficiency. This paper is the first to examine different type of bioethanol plant configurations including industrial symbiosis strategy in order to meet high sustainability standards and design robust and sustainable industrial symbiosis based hybrid generation bioethanol supply chains (ISHGBSC). A novel stochastic mixed integer linear programming (SMILP) model is proposed to design the optimal ISHGBSC under different sustainability standards. A case study of North Dakota (ND) in USA has been studied as an application of the proposed model. The results show that some sustainability standards are stronger than others in terms of the number of green sustainability requirements met. When stronger sustainability standards are applied, the economic performance of the ISHGBSC is sacrificed. The results provide a guideline for policymakers to determine the appropriate standard to use under different sustainable concerns, and for policymakers and investors the best ISHGSBC structure under each standard. In addition, the results provide investors a guideline to invest in different technologies under different sustainability standards. Sensitivity analyses is also conducted to provide deep understanding of the proposed ISHGBSC and to identify the factors that might impact the stability of the ISHGBSC under different standards.

[1]  N. Shah,et al.  A comprehensive approach to the design of ethanol supply chains including carbon trading effects. , 2012, Bioresource technology.

[2]  Turan Paksoy,et al.  A MULTI OBJECTIVE MODEL FOR OPTIMIZATION OF A GREEN SUPPLY CHAIN NETWORK , 2010 .

[3]  Michael Q. Wang,et al.  Life-cycle energy and greenhouse gas emission impacts of different corn ethanol plant types , 2007 .

[4]  A. Ramudhin,et al.  Design of sustainable supply chains under the emission trading scheme , 2012 .

[5]  Raymond R. Tan,et al.  MILP model for emergy optimization in EIP water networks , 2011 .

[6]  David K. Lambert,et al.  Logistical design of a regional herbaceous crop residue-based ethanol production complex. , 2010 .

[7]  Afsar Ali.  Strategies for sustainable development through education , 2015 .

[8]  Jun Zhang,et al.  Stochastic optimization of sustainable hybrid generation bioethanol supply chains , 2015, Transportation Research Part E: Logistics and Transportation Review.

[9]  Yong Jin,et al.  Modeling and Optimization of a Coal‐Chemical Eco‐industrial System in China , 2012 .

[10]  A. Wolf,et al.  Using an optimization model to evaluate the economic benefits of industrial symbiosis in the forest industry , 2008 .

[11]  Eddie Schrevens,et al.  Carbon and Water Footprints and Energy Use of Greenhouse Tomato Production in Northern Italy , 2014 .

[12]  May Wu,et al.  Energy and Emission Benefits of Alternative Transportation Liquid Fuels Derived from Switchgrass: A Fuel Life Cycle Assessment , 2006, Biotechnology progress.

[13]  Aldo R. Vecchietti,et al.  Optimal design for sustainable bioethanol supply chain considering detailed plant performance model , 2011, Comput. Chem. Eng..

[14]  R. Oloruntoba,et al.  Public Policy and Biofuels: The Way Forward? , 2007 .

[15]  David Simchi-Levi,et al.  Sustainable supply chain design: a closed-loop formulation and sensitivity analysis , 2012 .

[16]  N. Shah,et al.  Spatially Explicit Static Model for the Strategic Design of Future Bioethanol Production Systems. 1. Cost Minimization , 2009 .

[17]  L. B. E. Veiga,et al.  Eco-industrial park development in Rio de Janeiro, Brazil: a tool for sustainable development , 2009 .

[18]  Halit Üster,et al.  A closed-loop supply chain network design problem with integrated forward and reverse channel decisions , 2010 .

[19]  R. Perrin,et al.  Net energy of cellulosic ethanol from switchgrass , 2008, Proceedings of the National Academy of Sciences.

[20]  Guojun Ji.  Ecological Supply Chains Performance Evaluation and Disruption Risk Management Strategies , 2009 .

[21]  C. Adjiman,et al.  A spatially explicit whole-system model of the lignocellulosic bioethanol supply chain: an assessment of decentralised processing potential , 2008, Biotechnology for biofuels.

[22]  Ayhan Demirbas,et al.  Progress and recent trends in biofuels , 2007 .

[23]  Jun Zhang,et al.  Stochastic optimization of a multi-feedstock lignocellulosic-based bioethanol supply chain under multiple uncertainties , 2013 .

[24]  Gonzalo Guillén-Gosálbez,et al.  Multiobjective Model for More Sustainable Fuel Supply Chains. A Case Study of the Sugar Cane Industry in Argentina , 2011 .

[25]  A. Zamboni,et al.  Strategic design and investment capacity planning of the ethanol supply chain under price uncertainty. , 2011 .

[26]  Jun Zhang,et al.  Design of the optimal industrial symbiosis system to improve bioethanol production , 2014 .

[27]  Jay H. Lee,et al.  Optimal design and global sensitivity analysis of biomass supply chain networks for biofuels under uncertainty , 2011, Comput. Chem. Eng..

[28]  F. Boons,et al.  The dynamics of industrial symbiosis: A proposal for a conceptual framework based upon a comprehensive literature review , 2011 .

[29]  Sunwon Park,et al.  Optimization of a waste heat utilization network in an eco-industrial park , 2010 .

[30]  R. Tan,et al.  Game theory approach to the analysis of inter-plant water integration in an eco-industrial park , 2009 .

[31]  Lazaros G. Papageorgiou,et al.  Economic optimisation of a UK advanced biofuel supply chain , 2012 .

[32]  Serge Domenech,et al.  On the flexibility of an eco-industrial park (EIP) for managing industrial water , 2013 .

[33]  Fengqi You,et al.  Design under uncertainty of hydrocarbon biorefinery supply chains: Multiobjective stochastic programming models, decomposition algorithm, and a Comparison between CVaR and downside risk , 2012 .

[34]  Serge Domenech,et al.  Industrial water management by multiobjective optimization: from individual to collective solution through eco-industrial parks , 2012 .

[35]  Ryan Davis,et al.  Process Design and Economics for Biochemical Conversion of Lignocellulosic Biomass to Ethanol: Dilute-Acid Pretreatment and Enzymatic Hydrolysis of Corn Stover , 2011 .

[36]  Lazaros G. Papageorgiou,et al.  An optimisation framework for a hybrid first/second generation bioethanol supply chain , 2012, Comput. Chem. Eng..

[37]  W. Michael Griffin,et al.  Impacts of facility size and location decisions on ethanol production cost , 2011 .

[38]  H. Cai,et al.  Well-to-wheels energy use and greenhouse gas emissions of ethanol from corn, sugarcane and cellulosic biomass for US use , 2012 .

[39]  W. A. Marvin,et al.  Biorefinery location and technology selection through supply chain optimization , 2013 .

[40]  Lieve Helsen,et al.  Anaerobic digestion in global bio-energy production: Potential and research challenges , 2011 .

[41]  Catherine A. Hardy,et al.  Industrial Ecosystems as Food Webs , 2002 .

[42]  Halil I. Cobuloglu,et al.  A mixed-integer optimization model for the economic and environmental analysis of biomass production , 2014 .

[43]  Mahmoud M. El-Halwagi,et al.  Design and integration of eco‐industrial parks for managing water resources , 2009 .

[44]  Alexander Shapiro,et al.  The Sample Average Approximation Method for Stochastic Discrete Optimization , 2002, SIAM J. Optim..

[45]  R. Schnepf,et al.  Renewable Fuel Standard (Rfs): Overview and Issues , 2012 .

[46]  Wyatt Thompson,et al.  How does petroleum price and corn yield volatility affect ethanol markets with and without an ethanol use mandate , 2009 .

[47]  H. Stein,et al.  Distillers dried grains with solubles (DDGS) in diets fed to swine , 2007 .

[48]  Gonzalo Guillén-Gosálbez,et al.  Identifying key life cycle assessment metrics in the multiobjective design of bioethanol supply chains using a rigorous mixed-integer linear programming approach , 2012 .

[49]  Sara Giarola,et al.  Environmentally conscious capacity planning and technology selection for bioethanol supply chains , 2012 .

[50]  Irina Angelikadi,et al.  Monitoring and controlling the biogas process , 1997 .

[51]  Gang Xie,et al.  Modeling decision processes of a green supply chain with regulation on energy saving level , 2015, Comput. Oper. Res..

[52]  Fabrizio Bezzo,et al.  Spatially Explicit Multiobjective Optimization for the Strategic Design of First and Second Generation Biorefineries Including Carbon and Water Footprints , 2013 .

[53]  Yueyue Fan,et al.  Bioethanol supply chain system planning under supply and demand uncertainties , 2012 .

[54]  Fabrizio Bezzo,et al.  Spatially explicit multi-objective optimisation for design and planning of hybrid first and second generation biorefineries , 2011, Comput. Chem. Eng..

[55]  Cole R. Gustafson,et al.  The Viability of Harvesting Corn Cobs and Stover for Biofuel Production in North Dakota , 2011 .

[56]  F. You,et al.  Optimal design of sustainable cellulosic biofuel supply chains: Multiobjective optimization coupled with life cycle assessment and input–output analysis , 2012 .

[57]  Nilay Shah,et al.  Spatially Explicit Static Model for the Strategic Design of Future Bioethanol Production Systems. 2. Multi-Objective Environmental Optimization , 2009 .

[58]  David Chi Wai Hui,et al.  Use of Municipal Solid Waste for Integrated Cement Production , 2008 .

[59]  Douglas G. Tiffany,et al.  Biomass for Electricity and Process Heat at Ethanol Plants , 2005 .

[60]  Shahab Sokhansanj,et al.  Large‐scale production, harvest and logistics of switchgrass (Panicum virgatum L.) – current technology and envisioning a mature technology , 2009 .

[61]  Fabrizio Bezzo,et al.  Ethanol from corn: a technical and economical assessment based on different scenarios , 2008 .

[62]  Mohammed Moniruzzaman,et al.  Hydrolysis by commercial enzyme mixtures of AFEX-treated corn fiber and isolated xylans , 1997 .

[63]  Shih-Chang Tseng,et al.  A strategic decision-making model considering the social costs of carbon dioxide emissions for sustainable supply chain management. , 2014, Journal of environmental management.

[64]  P. Flynn,et al.  The relative cost of biomass energy transport , 2007, Applied biochemistry and biotechnology.

[65]  Jun Zhang,et al.  An integrated optimization model for switchgrass-based bioethanol supply chain , 2013 .

[66]  W. A. Marvin,et al.  Economic Optimization of a Lignocellulosic Biomass-to-Ethanol Supply Chain , 2012 .

[67]  Yongxi Huang,et al.  Sustainable Biofuel Supply Chain Planning and Management under Uncertainty , 2013 .

[68]  D. V. Beers,et al.  Industrial Symbiosis in the Australian Minerals Industry: The Cases of Kwinana and Gladstone , 2007 .

[69]  Yueyue Fan,et al.  Multistage Optimization of the Supply Chains of Biofuels , 2010 .

[70]  M. Himmel,et al.  Welcome to Biotechnology for Biofuels , 2008, Biotechnology for biofuels.

[71]  Halil I. Cobuloglu,et al.  Food vs. biofuel: An optimization approach to the spatio-temporal analysis of land-use competition and environmental impacts , 2015 .

[72]  W. K. George,et al.  University of Illinois at Urbana-Champain , 1997 .

[73]  Arjen Ysbert Hoekstra,et al.  The consumptive water footprint of electricity and heat: a global assessment , 2015 .

[74]  Jun Zhang,et al.  Stochastic production planning for a biofuel supply chain under demand and price uncertainties , 2013 .

[75]  A. Barbosa‐Póvoa,et al.  Towards supply chain sustainability: economic, environmental and social design and planning , 2015 .

[76]  Heungjo An,et al.  A mathematical model to design a lignocellulosic biofuel supply chain system with a case study based on a region in Central Texas. , 2011, Bioresource technology.

[77]  Yongxi Huang,et al.  Analysis of an imperfectly competitive cellulosic biofuel supply chain , 2014 .

[78]  Iddrisu Awudu,et al.  Uncertainties and sustainability concepts in biofuel supply chain management: A review , 2012 .

[79]  Sandra Duni Eksioglu,et al.  Analyzing the design and management of biomass-to-biorefinery supply chain , 2009, Comput. Ind. Eng..

[80]  Mats Eklund,et al.  Improving the environmental performance of biofuels with industrial symbiosis , 2011 .