Optimization and Simulation in Biofuel Supply Chainopen access
- Authors
- Kim, Youngjin; Kim, Sojung
- Issue Date
- Mar-2025
- Publisher
- MDPI
- Keywords
- renewable energy; biofuel; simulation; optimization; supply chain
- Citation
- Energies, v.18, no.5, pp 1 - 24
- Pages
- 24
- Indexed
- SCIE
SCOPUS
- Journal Title
- Energies
- Volume
- 18
- Number
- 5
- Start Page
- 1
- End Page
- 24
- URI
- https://scholarworks.dongguk.edu/handle/sw.dongguk/58021
- DOI
- 10.3390/en18051194
- ISSN
- 1996-1073
1996-1073
- 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.
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Collections - College of Engineering > Department of Industrial and Systems Engineering > 1. Journal Articles

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