Systematic approach for the design of sustainable supply chains under quality uncertainty

Abstract Sustainable processes have recently awaked an increasing interest in the process systems engineering literature. In industry, this kind of problems inevitably required a multi-objective analysis to evaluate the environmental impact in addition to the economic performance. Bio-based processes have the potential to enhance the sustainability level of the energy sector. Nevertheless, such processes very often show variable conditions and present an uncertain behavior. The approaches presented for solving multi-objective problems under uncertainty have neglected the potential effects of different quality streams on the overall system. Here, it is presented an alternative approach, based on a State Task Network formulation, capable of optimizing under uncertain conditions, considering multiple selection criteria and accounting for the material quality effect. The resulting set of Pareto solutions are then assessed using the Elimination and Choice Expressing Reality-IV method, which identify the ones showing better overall performance considering the uncertain parameters space.

[1]  Dražen Lončar,et al.  Dynamic modelling of biomass gasification in a co-current fixed bed gasifier , 2016 .

[2]  A. Faaij,et al.  International bioenergy transport costs and energy balance , 2005 .

[3]  Gonzalo Guillén-Gosálbez,et al.  A global optimization strategy for the environmentally conscious design of chemical supply chains under uncertainty in the damage assessment model , 2010, Comput. Chem. Eng..

[4]  Manosh C. Paul,et al.  Assessing biomass steam gasification technologies using a multi-purpose model , 2016 .

[5]  Luis Puigjaner,et al.  Strategic Planning of Biomass Supply Chain Networks for Co-combustion Plants , 2015 .

[6]  Erik Dahlquist,et al.  The influence of different parameters on biomass gasification in circulating fluidized bed gasifiers , 2016 .

[7]  Pu Li,et al.  Chance constrained programming approach to process optimization under uncertainty , 2008, Comput. Chem. Eng..

[8]  Tong Qiu,et al.  A study of the LCA based biofuel supply chain multi-objective optimization model with multi-conversion paths in China , 2014 .

[9]  N. Jacobsen.  Industrial Symbiosis in Kalundborg, Denmark: A Quantitative Assessment of Economic and Environmental Aspects , 2006 .

[10]  Gonzalo Guillén-Gosálbez,et al.  Optimal design and planning of sustainable chemical supply chains under uncertainty , 2009 .

[11]  Gonzalo Guillén-Gosálbez,et al.  Multiobjective optimization for designing and operating more sustainable water management systems for a city in Mexico , 2015 .

[12]  José Miguel Laínez,et al.  Flexible design‐planning of supply chain networks , 2009 .

[13]  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 .

[14]  John R. Birge,et al.  Introduction to Stochastic Programming , 1997 .

[15]  Maghsud Solimanpur,et al.  An integrated supply chain configuration model and procurement management under uncertainty: A set-based robust optimization methodology , 2016 .

[16]  Armand Baboli,et al.  Production , Manufacturing and Logistics A stochastic aggregate production planning model in a green supply chain : con ‐ sidering flexible lead times , nonlinear purchase and shortage cost functions , 2013 .

[17]  Gonzalo Guillén-Gosálbez,et al.  Using Pareto filters to support risk management in optimization under uncertainty: Application to the strategic planning of chemical supply chains , 2017, Comput. Chem. Eng..

[18]  Chen Lu,et al.  Improved decomposition-coordination and discrete differential dynamic programming for optimization of large-scale hydropower system , 2014 .

[19]  H. E. Stassen.  Small-Scale Biomass Gasifiers for Heat and Power: A Global Review , 1995 .

[20]  Rosnah Mohd Yusuff,et al.  Integrated supply chain planning under uncertainty using an improved stochastic approach , 2011 .

[21]  Pekka Salminen,et al.  ELECTRE III and IV Decision Aids in an Environmental Problem , 1997 .

[22]  Ali Shanian,et al.  A non-compensatory compromised solution for material selection of bipolar plates for polymer electrolyte membrane fuel cell (PEMFC) using ELECTRE IV , 2006 .

[23]  Luis Puigjaner,et al.  Design of regional and sustainable bio-based networks for electricity generation using a multi-objective MILP approach , 2012 .

[24]  Borja Velázquez-Martí,et al.  Analysis of the process of biomass harvesting with collecting- chippers fed by pick up headers in plantations of olive trees , 2009 .

[25]  Maria del Mar,et al.  Conceptual design of alternative energy systems from biomass , 2011 .

[26]  Antoon J. B. ten Kate.  PSE for problem solving excellence in industrial R&D , 2016, Comput. Chem. Eng..

[27]  Gonzalo Guillén-Gosálbez,et al.  Design and planning of infrastructures for bioethanol and sugar production under demand uncertainty , 2012 .

[28]  Fengqi You,et al.  Stochastic inventory management for tactical process planning under uncertainties: MINLP models and algorithms , 2011 .

[29]  Antonis C. Kokossis,et al.  e-Symbiosis: technology-enabled support for Industrial Symbiosis targeting Small and Medium Enterprises and innovation , 2015 .

[30]  R. V. Berkel,et al.  Quantifying Sustainability Benefits of Industrial Symbioses , 2010 .

[31]  André Faaij,et al.  Future prospects for production of methanol and hydrogen from biomass , 2002 .

[32]  Martin Gutsch,et al.  Uncertainty of biomass contributions from agriculture and forestry to renewable energy resources under climate change , 2015 .

[33]  Martin Rogers,et al.  Electre and decision support : methods and applications in engineering and infrastructure investment , 2000 .

[34]  B. Roy.  THE OUTRANKING APPROACH AND THE FOUNDATIONS OF ELECTRE METHODS , 1991 .

[35]  José Miguel Laínez,et al.  Incorporating environmental impacts and regulations in a holistic supply chains modeling: An LCA approach , 2009, Comput. Chem. Eng..

[36]  J. Ehrenfeld,et al.  Organizing Self‐Organizing Systems , 2012 .

[37]  Salvatore Greco,et al.  An Overview of ELECTRE Methods and their Recent Extensions , 2013 .

[38]  A. Shapiro,et al.  The Sample Average Approximation Method for Stochastic Programs with Integer Recourse , 2002 .

[39]  John R. Birge,et al.  Introduction to Stochastic programming (2nd edition), Springer verlag, New York , 2011 .

[40]  Fernando P. Bernardo,et al.  Value of information analysis in product/process design , 2004 .