Data aggregation tool for use in milp biomass supply chain optimization

2018 ◽  
Vol 02 ◽  
Author(s):  
Nathanial Cooper ◽  
Anna Panteli ◽  
Nilay Shah
2017 ◽  
Vol 47 (3) ◽  
pp. 277-288 ◽  
Author(s):  
Luana Dessbesell ◽  
Chunbao (Charles) Xu ◽  
Reino Pulkki ◽  
Mathew Leitch ◽  
Nubla Mahmood

Technological development has enabled the production of new value-added products from lignocellulosic residues such as lignin. This has allowed the forest industry to diversify its product portfolio and maximize the economic returns from feedstock, while simultaneously working towards sustainable alternatives to petroleum-based products. Although previous research has explored industrial-scale production opportunities, many challenges persist, including the cost of woody biomass and its supply chain reliability. While numerous studies have addressed these issues, their emphasis has traditionally been on bioenergy, with little focus on biochemical, biomaterials, and bioproducts. This review seeks to address this gap through a systematic study of the work recently reported by researchers. A lot of work has been published from United States and Canada with an emphasis on bioenergy production (84.8%), 4.6% of the work is focused on biomass to materials and chemicals, and 10.6% addressed both. Between 2012 and 2015, the majority of published research focused on biomass to materials and chemicals and both biomass to energy and biomass to materials and chemicals. This fact highlights recent interests in diversified biorefinery portfolios. However, further work concerning forest biomass supply chain optimization and new high-value bio-based materials and chemicals is necessary.


2019 ◽  
Author(s):  
Nathanial Cooper ◽  
Anna Panteli ◽  
Nilay Shah

Abstract Biomass and the bio-economy have strong potential to help shift dependency away from petroleum. Supply chain optimisation (SCO) has been used to help other industries and can be used to boost biomass industry viability. Biomass supply chain models frequently average the biomass yield of large tracts of land in their calculations. However, there can be large variation in the biomass yield within those tracts, losing useful information. This work presents a biomass SCO framework which approximates the available quality of land by piecewise linearly approximation of the biomass yield distribution, and incorporates this information into the optimisation. The linear estimates of the biomass yield distributions allow the SCO model to make more informed decisions about quantity and location of biomass growth operations, affecting all downstream decisions. A case study of mainland Great Britain has been examined using the framework to illustrate the impact of retaining biomass yield information in the optimisation, versus averaging the yield across tracts of land. The case study found that using biomass yield linear estimates reduced the overall land usage by 10%. Further, it improved biomass output, which increased the quantity of bio-products produced. All of this led to an increase in the overall profit.


2015 ◽  
Vol 70 ◽  
pp. 138-148 ◽  
Author(s):  
Tao Lin ◽  
Shaowen Wang ◽  
Luis F. Rodríguez ◽  
Hao Hu ◽  
Yan Liu

Energy ◽  
2021 ◽  
pp. 122374
Author(s):  
Juanjuan Wu ◽  
Jian Zhang ◽  
Weiming Yi ◽  
Hongzhen Cai ◽  
Yang Li ◽  
...  

2005 ◽  
Vol 29 (6) ◽  
pp. 1305-1316 ◽  
Author(s):  
E.P. Schulz ◽  
M.S. Diaz ◽  
J.A. Bandoni

2016 ◽  
Vol 83 ◽  
pp. 1-11 ◽  
Author(s):  
Annelies De Meyer ◽  
Monique Snoeck ◽  
Dirk Cattrysse ◽  
Jos Van Orshoven

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