Evaluating refinery supply chain policies and investment decisions through simulation-optimization
Authors: 
Lee Ying Koo, Yuhong Chen, Arief Adhitya, Rajagopalan Srinivasan, Iftekhar A. KarimiAuthors Info & Claims
Pages 1431 - 1437
Abstract
The dynamic, non-linear, and complex nature of a supply chain with numerous interactions among its entities are best evaluated using simulation models. The optimization of such system is not amenable to mathematical programming approaches. The simulation-optimization method seems to be the most promising. In this paper, we look at a refinery supply chain simulation and attempt to optimize the refinery operating policies and capacity investments by employing a genetic algorithm. The refinery supply chain is complex with multiple, distributed, and disparate entities which operate their functions based on certain policies. Policy and investment decisions have significant impact on the refinery bottom line. To optimize them, we develop a simple simulation-optimization framework by combining the refinery supply chain simulator called Integrated Refinery In Silico (IRIS) and genetic algorithm. Results indicate that the proposed framework works well for optimization of supply chain policy and investment decisions.
References
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Banks, J., S. Buckley, S. Jain, and P. Lendermann 2002. Panel session: opportunities for simulation in supply chain management. In Proceedings of the 2002 Winter Simulation Conference, eds. E. Yücesan, C. H. Chen, J. L. Snowdon, and J. M. Charnes, 1652--1658. Piscataway, New Jersey: Institute of Electrical and Electronics Engineers.
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- Evaluating refinery supply chain policies and investment decisions through simulation-optimization
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Information
Published In
December 2006
2429 pages
ISBN:1424405017
- Editors:
- L. Felipe Perrone,
- Barry G. Lawson,
- Jason Liu,
- Frederick P. Wieland,
- General Chair:
- David Nicol,
- Program Chair:
- Richard Fujimoto
Sponsors
- IIE: Institute of Industrial Engineers
- ASA: American Statistical Association
- IEICE ESS: Institute of Electronics, Information and Communication Engineers, Engineering Sciences Society
- IEEE-CS\DATC: The IEEE Computer Society
- SIGSIM: ACM Special Interest Group on Simulation and Modeling
- NIST: National Institute of Standards and Technology
- (SCS): The Society for Modeling and Simulation International
- INFORMS-CS: Institute for Operations Research and the Management Sciences-College on Simulation
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Winter Simulation Conference
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Published: 03 December 2006
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WSC06
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- IIE
- ASA
- IEICE ESS
- IEEE-CS\DATC
- SIGSIM
- NIST
- (SCS)
- INFORMS-CS
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WSC '06 Paper Acceptance Rate 177 of 252 submissions, 70%;
Overall Acceptance Rate 3,413 of 5,075 submissions, 67%
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