Location Allocation of Corn Stover Pretreatment Facilities in South Korea Under an Agent-Based Simulation Framework
This research proposes a novel location allocation framework that utilizes agent-based simulation for the efficient production of corn stover-based bioethanol, which requires dedicated pretreatment facilities for the feedstock. The framework comprises two main modules: (1) a Pretreatment Facility Mo...
Saved in:
| Published in | Applied sciences Vol. 15; no. 17; p. 9488 |
|---|---|
| Main Authors | , , |
| Format | Journal Article |
| Language | English |
| Published |
29.08.2025
|
| Online Access | Get full text |
| ISSN | 2076-3417 2076-3417 |
| DOI | 10.3390/app15179488 |
Cover
| Abstract | This research proposes a novel location allocation framework that utilizes agent-based simulation for the efficient production of corn stover-based bioethanol, which requires dedicated pretreatment facilities for the feedstock. The framework comprises two main modules: (1) a Pretreatment Facility Module that assesses the performance of the corn stover-based bioethanol supply chain based on the interactions among three types of agents, namely order agent, pretreatment agent, and transport agent, and (2) an Optimization Module designed to determine the optimal supply chain configuration by selecting the most suitable number and locations for pretreatment facilities to achieve the lowest total operational cost. The framework is implemented in a case study for South Korea, which aims to raise the bioethanol blending ratio from 4% in 2025 to 8% by 2030. Experimental results reveal that, within the bioethanol supply chain comprising eight farms and four refineries, a 1% increase in bioethanol blending ratio leads to an increase in the demand for approximately 2229 kL of ethanol (10,225 tons of corn stover), and the proposed framework enables to identify the optimal location of pretreatment facilities in the subject supply chain according to the change in ethanol demand. |
|---|---|
| AbstractList | This research proposes a novel location allocation framework that utilizes agent-based simulation for the efficient production of corn stover-based bioethanol, which requires dedicated pretreatment facilities for the feedstock. The framework comprises two main modules: (1) a Pretreatment Facility Module that assesses the performance of the corn stover-based bioethanol supply chain based on the interactions among three types of agents, namely order agent, pretreatment agent, and transport agent, and (2) an Optimization Module designed to determine the optimal supply chain configuration by selecting the most suitable number and locations for pretreatment facilities to achieve the lowest total operational cost. The framework is implemented in a case study for South Korea, which aims to raise the bioethanol blending ratio from 4% in 2025 to 8% by 2030. Experimental results reveal that, within the bioethanol supply chain comprising eight farms and four refineries, a 1% increase in bioethanol blending ratio leads to an increase in the demand for approximately 2229 kL of ethanol (10,225 tons of corn stover), and the proposed framework enables to identify the optimal location of pretreatment facilities in the subject supply chain according to the change in ethanol demand. |
| Author | Kim, Youngjin Seo, Junyoung Kim, Sojung |
| Author_xml | – sequence: 1 givenname: Youngjin orcidid: 0000-0001-9222-4789 surname: Kim fullname: Kim, Youngjin – sequence: 2 givenname: Junyoung surname: Seo fullname: Seo, Junyoung – sequence: 3 givenname: Sojung orcidid: 0000-0001-7744-0686 surname: Kim fullname: Kim, Sojung |
| BookMark | eNpNkMFKAzEQhoMoWGtPvkDuspo0ySZ7rMWqWFBoPS9pMtHo7qYkqeLbG6lC5zI_Mx_f4T9Dx0MYAKELSq4Ya8i13m6poLLhSh2h0ZTIumKcyuODfIomKb2TMg1lipIRSstgdPZhwLOu-4_B4XmIA17l8AkRP0fIEXTuYch4oY3vfPaQsC9E2OU3_BjKG78MtsC6mF4LWN3oBBavfL_r9tZF1D18hfhxjk6c7hJM_vYYrRe36_l9tXy6e5jPlpWRTFVGEAXEgDVOUTvlWtRCbehGMafplBDGmBNWcC641UBrR6zjpNHlIGW9kWyMLvdaE0NKEVy7jb7X8bulpP1trD1ojP0AGLVhLg |
| Cites_doi | 10.1016/j.biombioe.2009.05.025 10.4028/www.scientific.net/AMR.785-786.1473 10.1016/j.biombioe.2024.107220 10.1016/j.biortech.2019.122724 10.1016/j.sca.2023.100042 10.1016/j.rser.2019.01.048 10.1186/1754-6834-2-30 10.1016/j.rser.2021.111911 10.3389/fbioe.2020.00716 10.1109/WSC.2013.6721625 10.1007/s12155-015-9662-6 10.1016/j.esr.2018.08.006 10.1016/j.biortech.2017.02.068 10.3390/su11133604 10.1007/s11367-015-0985-5 10.1002/bit.21132 10.1016/j.esd.2024.101598 10.1016/j.resconrec.2019.104652 10.1016/j.biortech.2013.12.091 10.1016/j.jenvman.2023.118279 10.1016/j.pecs.2018.03.004 10.1016/j.fuproc.2019.106244 10.18331/BRJ2017.4.4.4 10.1016/j.rser.2014.04.047 10.1021/acssuschemeng.7b03303 10.1016/j.fuproc.2016.12.007 10.1109/WSC.2010.5679168 10.1002/bbb.1954 10.3390/en12081422 10.1016/j.biortech.2023.128856 10.1016/j.biombioe.2021.106276 10.1002/tqem.22336 10.1016/j.jclepro.2017.08.126 10.1016/j.biortech.2019.01.112 10.3390/en15186512 10.1016/j.biortech.2005.01.017 10.1016/j.eneco.2012.01.003 10.1016/j.rser.2018.03.111 10.1016/j.cej.2025.159731 10.1016/j.jclepro.2020.121327 10.1016/j.simpat.2018.05.006 10.1016/j.rser.2013.12.036 10.1016/j.tranpol.2020.10.007 10.1021/ie5020519 10.1016/j.biombioe.2022.106447 10.1016/j.renene.2016.05.009 |
| ContentType | Journal Article |
| DBID | AAYXX CITATION |
| DOI | 10.3390/app15179488 |
| DatabaseName | CrossRef |
| DatabaseTitle | CrossRef |
| DatabaseTitleList | CrossRef |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Engineering Sciences (General) |
| EISSN | 2076-3417 |
| ExternalDocumentID | 10_3390_app15179488 |
| GroupedDBID | .4S 2XV 5VS 7XC 8CJ 8FE 8FG 8FH AADQD AAFWJ AAYXX ADBBV ADMLS AFKRA AFPKN AFZYC ALMA_UNASSIGNED_HOLDINGS APEBS ARCSS BCNDV BENPR CCPQU CITATION CZ9 D1I D1J D1K GROUPED_DOAJ IAO IGS ITC K6- K6V KC. KQ8 L6V LK5 LK8 M7R MODMG M~E OK1 P62 PHGZM PHGZT PIMPY PROAC PUEGO TUS |
| ID | FETCH-LOGICAL-c738-c508e0cedcf81d24a5658b1b83fa1200333f5d54454dae16f0df409a445776b73 |
| ISSN | 2076-3417 |
| IngestDate | Wed Sep 03 16:36:26 EDT 2025 |
| IsDoiOpenAccess | false |
| IsOpenAccess | true |
| IsPeerReviewed | true |
| IsScholarly | true |
| Issue | 17 |
| Language | English |
| License | https://creativecommons.org/licenses/by/4.0 |
| LinkModel | OpenURL |
| MergedId | FETCHMERGED-LOGICAL-c738-c508e0cedcf81d24a5658b1b83fa1200333f5d54454dae16f0df409a445776b73 |
| ORCID | 0000-0001-7744-0686 0000-0001-9222-4789 |
| OpenAccessLink | https://www.mdpi.com/2076-3417/15/17/9488/pdf?version=1756480732 |
| ParticipantIDs | crossref_primary_10_3390_app15179488 |
| PublicationCentury | 2000 |
| PublicationDate | 2025-08-29 |
| PublicationDateYYYYMMDD | 2025-08-29 |
| PublicationDate_xml | – month: 08 year: 2025 text: 2025-08-29 day: 29 |
| PublicationDecade | 2020 |
| PublicationTitle | Applied sciences |
| PublicationYear | 2025 |
| References | Eggeman (ref_34) 2005; 96 ref_14 Zabed (ref_31) 2019; 105 ref_58 ref_13 ref_57 ref_12 ref_56 ref_11 ref_55 ref_10 Singh (ref_46) 2014; 53 ref_54 ref_53 Chen (ref_38) 2017; 160 ref_52 ref_51 Behera (ref_29) 2014; 36 ref_19 ref_17 ref_16 ref_15 ref_59 Prasad (ref_3) 2014; 84 Costa (ref_44) 2017; 167 Cattrysse (ref_49) 2014; 31 Galvan (ref_77) 2024; 83 Ng (ref_39) 2017; 100 ref_61 ref_60 Hegde (ref_33) 2019; 13 Yoo (ref_67) 2016; 9 Kumar (ref_30) 2020; 199 Zhao (ref_37) 2020; 155 ref_69 ref_22 Bai (ref_47) 2012; 34 ref_66 ref_21 ref_20 ref_63 Zhang (ref_18) 2025; 505 Prasad (ref_27) 2016; 21 Helo (ref_50) 2023; 4 Chen (ref_68) 2009; 33 ref_71 ref_36 ref_35 Zhao (ref_65) 2018; 67 ref_76 Kim (ref_23) 2021; 100 ref_74 Zhao (ref_70) 2014; 155 Lozano (ref_73) 2018; 6 Kim (ref_45) 2018; 86 Lin (ref_41) 2020; 262 Ranisau (ref_42) 2017; 4 Yu (ref_26) 2019; 279 Yang (ref_72) 2013; 785 Fansuri (ref_25) 2024; 34 Kwon (ref_62) 2023; 342 Kumari (ref_28) 2018; 90 Habibi (ref_43) 2018; 22 Baral (ref_32) 2017; 232 Fu (ref_75) 2022; 15 ref_40 ref_1 Kim (ref_24) 2022; 155 ref_2 ref_48 ref_9 ref_8 Chundawat (ref_64) 2007; 96 ref_5 ref_4 ref_7 ref_6 |
| References_xml | – ident: ref_9 – ident: ref_74 – ident: ref_5 – ident: ref_55 – volume: 33 start-page: 1381 year: 2009 ident: ref_68 article-title: Comparison of four different chemical pretreatments of corn stover for enhancing enzymatic digestibility publication-title: Biomass Bioenerg. doi: 10.1016/j.biombioe.2009.05.025 – volume: 785 start-page: 1473 year: 2013 ident: ref_72 article-title: Supply chain coordination mechanism logistics cost optimization analysis publication-title: Adv. Mater. Res. doi: 10.4028/www.scientific.net/AMR.785-786.1473 – ident: ref_1 doi: 10.1016/j.biombioe.2024.107220 – ident: ref_36 doi: 10.1016/j.biortech.2019.122724 – volume: 4 start-page: 100042 year: 2023 ident: ref_50 article-title: An agent-based simulation and logistics optimization model for managing uncertain demand in forest supply chains publication-title: Supply Chain Anal. doi: 10.1016/j.sca.2023.100042 – ident: ref_61 – volume: 105 start-page: 105 year: 2019 ident: ref_31 article-title: Recent advances in biological pretreatment of microalgae and lignocellulosic biomass for biofuel production publication-title: Renew. Sust. Energ. Rev. doi: 10.1016/j.rser.2019.01.048 – ident: ref_69 doi: 10.1186/1754-6834-2-30 – ident: ref_58 – volume: 155 start-page: 111911 year: 2022 ident: ref_24 article-title: Hybrid simulation framework for the production management of an ethanol biorefinery publication-title: Renew. Sust. Energ. Rev. doi: 10.1016/j.rser.2021.111911 – ident: ref_63 doi: 10.3389/fbioe.2020.00716 – ident: ref_71 doi: 10.1109/WSC.2013.6721625 – volume: 9 start-page: 67 year: 2016 ident: ref_67 article-title: Understanding the physicochemical characteristics and the improved enzymatic saccharification of corn stover pretreated with aqueous and gaseous ammonia publication-title: BioEnergy Res. doi: 10.1007/s12155-015-9662-6 – ident: ref_8 – volume: 22 start-page: 82 year: 2018 ident: ref_43 article-title: A location-inventory-routing optimization model for cost effective design of microalgae biofuel distribution system: A case study in Iran publication-title: Energy Strateg. Rev. doi: 10.1016/j.esr.2018.08.006 – ident: ref_4 – volume: 232 start-page: 331 year: 2017 ident: ref_32 article-title: Comparative techno-economic analysis of steam explosion, dilute sulfuric acid, ammonia fiber explosion and biological pretreatments of corn stover publication-title: Bioresour. Technol. doi: 10.1016/j.biortech.2017.02.068 – ident: ref_35 doi: 10.3390/su11133604 – ident: ref_56 – ident: ref_52 – volume: 21 start-page: 44 year: 2016 ident: ref_27 article-title: Life cycle assessment of lignocellulosic biomass pretreatment methods in biofuel production publication-title: Int. J. Life Cycle Assess. doi: 10.1007/s11367-015-0985-5 – ident: ref_48 – ident: ref_10 – volume: 96 start-page: 219 year: 2007 ident: ref_64 article-title: Effect of particle size based separation of milled corn stover on AFEX pretreatment and enzymatic digestibility publication-title: Biotechnol. Bioeng. doi: 10.1002/bit.21132 – volume: 83 start-page: 101598 year: 2024 ident: ref_77 article-title: GHG emissions intensity analysis. Case study: Bioethanol plant with cogeneration and partial CO2 recovery publication-title: Energy Sustain. Dev. doi: 10.1016/j.esd.2024.101598 – volume: 155 start-page: 104652 year: 2020 ident: ref_37 article-title: Bioethanol from corn stover—Integrated environmental impacts of alternative biotechnologies publication-title: Resour. Conserv. Recycl. doi: 10.1016/j.resconrec.2019.104652 – volume: 155 start-page: 34 year: 2014 ident: ref_70 article-title: Effects of compositional changes of AFEX-treated and H-AFEX-treated corn stover on enzymatic digestibility publication-title: Bioresour. Technol. doi: 10.1016/j.biortech.2013.12.091 – volume: 342 start-page: 118279 year: 2023 ident: ref_62 article-title: Organic waste derived bioethanol supply chain network: Multiobjective snapshot model with a real-Korea case study publication-title: J. Environ. Manag. doi: 10.1016/j.jenvman.2023.118279 – volume: 67 start-page: 275 year: 2018 ident: ref_65 article-title: Bioethanol from corn stover—a review and technical assessment of alternative biotechnologies publication-title: Prog. Energy Combust. Sci. doi: 10.1016/j.pecs.2018.03.004 – ident: ref_66 – ident: ref_13 – volume: 199 start-page: 106244 year: 2020 ident: ref_30 article-title: Current perspective on pretreatment technologies using lignocellulosic biomass: An emerging biorefinery concept publication-title: Fuel Process. Technol. doi: 10.1016/j.fuproc.2019.106244 – ident: ref_20 – ident: ref_59 – volume: 15 start-page: 200111 year: 2022 ident: ref_75 article-title: Can corn stover bioethanol production substantially contribute to China’s carbon neutrality ambition? publication-title: Resour. Conserv. Recyl. Adv. – volume: 4 start-page: 721 year: 2017 ident: ref_42 article-title: Optimization of biofuel production from corn stover under supply uncertainty in Ontario publication-title: Biofuel Res. J. doi: 10.18331/BRJ2017.4.4.4 – ident: ref_7 – volume: 36 start-page: 91 year: 2014 ident: ref_29 article-title: Importance of chemical pretreatment for bioconversion of lignocellulosic biomass publication-title: Renew. Sust. Energ. Rev. doi: 10.1016/j.rser.2014.04.047 – ident: ref_53 – volume: 6 start-page: 3331 year: 2018 ident: ref_73 article-title: Facilities location for residual biomass production system using geographic information system under uncertainty publication-title: ACS Sustain. Chem. Eng. doi: 10.1021/acssuschemeng.7b03303 – volume: 160 start-page: 196 year: 2017 ident: ref_38 article-title: A review on the pretreatment of lignocellulose for high-value chemicals publication-title: Fuel Process. Technol. doi: 10.1016/j.fuproc.2016.12.007 – ident: ref_51 doi: 10.1109/WSC.2010.5679168 – ident: ref_76 – volume: 13 start-page: 740 year: 2019 ident: ref_33 article-title: Challenges in lipid production from lignocellulosic biomass using Rhodosporidium sp.; A look at the role of lignocellulosic inhibitors publication-title: Biofuels Bioprod. Biorefin. doi: 10.1002/bbb.1954 – ident: ref_19 doi: 10.3390/en12081422 – ident: ref_16 doi: 10.1016/j.biortech.2023.128856 – ident: ref_17 doi: 10.1016/j.biombioe.2021.106276 – volume: 34 start-page: e22336 year: 2024 ident: ref_25 article-title: A review of the technological aspects and process optimization of bioethanol production from corn stover biomass: Pretreatment process, hydrolysis, fermentation, purification process, and future perspective publication-title: Environ. Qual. Manag. doi: 10.1002/tqem.22336 – ident: ref_11 – volume: 167 start-page: 174 year: 2017 ident: ref_44 article-title: A decisional simulation-optimization framework for sustainable facility location of a biodiesel plant in Colombia publication-title: J. Clean Prod. doi: 10.1016/j.jclepro.2017.08.126 – volume: 84 start-page: 1443 year: 2014 ident: ref_3 article-title: Biofuels production: A sustainable solution to combat climate change publication-title: Indian J. Agric. Sci. – ident: ref_40 – volume: 279 start-page: 10 year: 2019 ident: ref_26 article-title: Process integration for ethanol production from corn and corn stover as mixed substrates publication-title: Bioresour. Technol. doi: 10.1016/j.biortech.2019.01.112 – ident: ref_14 – ident: ref_21 – ident: ref_22 doi: 10.3390/en15186512 – volume: 96 start-page: 2019 year: 2005 ident: ref_34 article-title: Process and economic analysis of pretreatment technologies publication-title: Bioresour. Technol. doi: 10.1016/j.biortech.2005.01.017 – ident: ref_6 – volume: 34 start-page: 1623 year: 2012 ident: ref_47 article-title: Biofuel supply chain design under competitive agricultural land use and feedstock market equilibrium publication-title: Energy Econ. doi: 10.1016/j.eneco.2012.01.003 – volume: 90 start-page: 877 year: 2018 ident: ref_28 article-title: Pretreatment of lignocellulosic wastes for biofuel production: A critical review publication-title: Renew. Sust. Energ. Rev. doi: 10.1016/j.rser.2018.03.111 – ident: ref_54 – ident: ref_2 – volume: 505 start-page: 159731 year: 2025 ident: ref_18 article-title: High throughput pretreatment of corn stover using compacted biomass with recycled ammonia (COBRA) process publication-title: Chem. Eng. J. doi: 10.1016/j.cej.2025.159731 – ident: ref_12 – volume: 262 start-page: 121327 year: 2020 ident: ref_41 article-title: Forest biomass-to-biofuel factory location problem with multiple objectives considering environmental uncertainties and social enterprises publication-title: J. Clean Prod. doi: 10.1016/j.jclepro.2020.121327 – volume: 86 start-page: 155 year: 2018 ident: ref_45 article-title: Two-phase simulation-based location-allocation optimization of biomass storage distribution publication-title: Simul. Model. Pract. Theory doi: 10.1016/j.simpat.2018.05.006 – volume: 31 start-page: 657 year: 2014 ident: ref_49 article-title: Methods to optimise the design and management of biomass-for-bioenergy supply chains: A review publication-title: Renew. Sust. Energ. Rev. doi: 10.1016/j.rser.2013.12.036 – volume: 100 start-page: 89 year: 2021 ident: ref_23 article-title: Impacts of transportation and industrial complexes on establishment-level productivity growth in Korea publication-title: Transp. Policy doi: 10.1016/j.tranpol.2020.10.007 – volume: 53 start-page: 15111 year: 2014 ident: ref_46 article-title: Biorefinery supply chain network design under competitive feedstock markets: An agent-based simulation and optimization approach publication-title: Ind. Eng. Chem. Res. doi: 10.1021/ie5020519 – ident: ref_15 doi: 10.1016/j.biombioe.2022.106447 – ident: ref_60 – volume: 100 start-page: 90 year: 2017 ident: ref_39 article-title: Design of biofuel supply chains with variable regional depot and biorefinery locations publication-title: Renew. Energy doi: 10.1016/j.renene.2016.05.009 – ident: ref_57 |
| SSID | ssj0000913810 |
| Score | 2.3281589 |
| Snippet | This research proposes a novel location allocation framework that utilizes agent-based simulation for the efficient production of corn stover-based bioethanol,... |
| SourceID | crossref |
| SourceType | Index Database |
| StartPage | 9488 |
| Title | Location Allocation of Corn Stover Pretreatment Facilities in South Korea Under an Agent-Based Simulation Framework |
| Volume | 15 |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| link | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV1LT9wwELZauLSHqkCrAi3ygUNRlDZvJ8elAiEKqIJF4rbyU1oEmxUsh_LrO2M7ibvaA-0lihzHina-nRmPv5khZJ-XmcxMZmItjYwLZfK4qQWLE6GUAYErnWC-8_lFdXJdnN6UN8OJrs0uWYhv8nllXsn_SBXGQK6YJfsPku0XhQG4B_nCFSQM1xfJ-Kx1AbdodHfX3SK9on3AvrxIzkSKxcAlP-YSqbBTS8KKbPe86GcLjyPb_iiC__oIU63iQ7Bt4IhO731zL_RvHYcrdGY7D9Zb0eFYyHVotorkdtqj78qFZU-fZr_xydLsq_a2G_RBiKzEqKqPVFhdlSWsisEgOtupV4x1yrYMQcUC1dkUrr_fsk7P8wZJkHw-T7GcmJ_1d-XsJYvW8wxhh4OvT4KXX5P1jDE80V8_PLr4ddkH5LBAam2rV_Qf7vI5cYXvwQqBBxO4IuP35J3fQ9CRA8QGeaVnm-RtUFlyk2x4nf1Iv_rC4gdb5LHDCx3wQltDES_U4YWGeKEDXugUZiBeqMULtXihHFYa8EIHvNAeLx_I-Pho_OMk9k03YsnA9klw2HUitZIGdjJZwcHhr0Uq6tzwFImMeW5KhRWcCsV1WplEmSJpOAwwVgmWfyRrs3amPxEqjJLg7me1lHWRFlykTAldNUawVCVGbZP97neczF1plckKge28bNoueTMA8zNZWzw86S_gLy7Enpf0no23_AGviHCN |
| linkProvider | ProQuest |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Location+Allocation+of+Corn+Stover+Pretreatment+Facilities+in+South+Korea+Under+an+Agent-Based+Simulation+Framework&rft.jtitle=Applied+sciences&rft.au=Kim%2C+Youngjin&rft.au=Seo%2C+Junyoung&rft.au=Kim%2C+Sojung&rft.date=2025-08-29&rft.issn=2076-3417&rft.eissn=2076-3417&rft.volume=15&rft.issue=17&rft.spage=9488&rft_id=info:doi/10.3390%2Fapp15179488&rft.externalDBID=n%2Fa&rft.externalDocID=10_3390_app15179488 |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=2076-3417&client=summon |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=2076-3417&client=summon |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=2076-3417&client=summon |