Optimization and Simulation in Biofuel Supply Chain
Youngjin Kim and
Sojung Kim ()
Additional contact information
Youngjin Kim: Department of Industrial and Systems Engineering, Dongguk University-Seoul, Seoul 04620, Republic of Korea
Sojung Kim: Department of Industrial and Systems Engineering, Dongguk University-Seoul, Seoul 04620, Republic of Korea
Energies, 2025, vol. 18, issue 5, 1-24
Abstract:
Optimization is a key management science methodology utilizing mathematical techniques to determine optimal solutions to a variety of management challenges. The biofuel production process, comparable to existing supply chain operations, consists of complex interconnected activities among three principal components: farms, distribution networks, and refineries. To effectively manage the complex and large-scale biofuel supply chain network, it is essential to employ optimization methodologies such as linear programming and nonlinear programming. However, existing optimization methods are predominantly systematized for generalized issues such as manufacturing production scheduling and supply chain operations management, thus a systematic guideline indicating which techniques should be employed for specific problems in biofuel production and supply relative to the production and management of new and renewable energy sources is absent. Given the crucial need for a continuous increase in biofuel production and efficient management, optimization methods should be implemented. Accordingly, this study compiles optimization techniques suitable for biofuel supply chain operations through a thorough literature review. Particularly, this study examines methods ranging from conventional linear and nonlinear programming to recently utilized simulation-based optimization techniques, spurred by advancements in computing performance. Consequently, researchers and engineers will be equipped to select and implement suitable optimization methods for various challenges in the biofuel production process.
Keywords: renewable energy; biofuel; simulation; optimization; supply chain (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
References: View references in EconPapers View complete reference list from CitEc
Citations:
Downloads: (external link)
https://www.mdpi.com/1996-1073/18/5/1194/pdf (application/pdf)
https://www.mdpi.com/1996-1073/18/5/1194/ (text/html)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:18:y:2025:i:5:p:1194-:d:1602583
Access Statistics for this article
Energies is currently edited by Ms. Agatha Cao
More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().