Optimal number and location of storage hubs and biogas production reactors in farmlands with allocation of multiple feedstocks
Applied Mathematical Modelling, ISSN: 0307-904X, Vol: 55, Page: 447-465
2018
- 25Citations
- 93Usage
- 103Captures
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
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Metrics Details
- Citations25
- Citation Indexes25
- 25
- CrossRef14
- Usage93
- Downloads88
- Abstract Views5
- Captures103
- Readers103
- 103
Article Description
This paper focuses on the problem for designing a logistics system for bio-methane gas (BMG) production. In practice, farm residues such as crop residue, wood residue, and livestock manure are used in reactors as reactants to generate BMG. A multi-residue, multi-hub, multi-reactor location-allocation model is developed to design the logistics of BMG production system. Both the hubs’ and reactors’ locations, and the residue's distribution plan are investigated to minimize the total construction and logistical cost. The costs of construction, transportation, feedstocks and labor are taken into consideration to reflect the lifecycle cost of the entire undertaking. In this paper, a mixed-integer nonlinear problem is proposed to simulate a BMG production supply chain. In addition to the optimal solution methods, a search-based heuristic was also proposed to determine the locations of hubs and reactors for large instances and along with a proper allocation of residues that are transported from the farms to the hubs to the reactors. Several numerical examples are tested to evaluate the performance of the heuristic as well.
Bibliographic Details
http://www.sciencedirect.com/science/article/pii/S0307904X17307011; http://dx.doi.org/10.1016/j.apm.2017.11.010; http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85039438371&origin=inward; https://linkinghub.elsevier.com/retrieve/pii/S0307904X17307011; https://repository.lsu.edu/ag_econ_pubs/97; https://repository.lsu.edu/cgi/viewcontent.cgi?article=1096&context=ag_econ_pubs; https://digitalcommons.lsu.edu/ag_econ_pubs/97; https://digitalcommons.lsu.edu/cgi/viewcontent.cgi?article=1096&context=ag_econ_pubs; https://dx.doi.org/10.1016/j.apm.2017.11.010
Elsevier BV
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