TY - JOUR
T1 - Corporate dashboards for integrated business and engineering decisions in oil refineries
T2 - An agent-based approach
AU - Hu, W.
AU - Almansoori, A.
AU - Kannan, P. K.
AU - Azarm, S.
AU - Wang, Z.
N1 - Funding Information:
P. K. Kannan is Ralph J. Tyser Professor of Marketing Science, Smith School of Business, University of Maryland, College Park, Maryland, and he is the Chair of the Department of Marketing. His current research stream focuses on new product/service development, design and pricing of digital products and product lines, marketing and product development on the Internet, e-service, and customer relationship management (CRM) and customer loyalty. He has received several grants from National Science Foundation (NSF), Mellon Foundation, SAIC, and PricewaterhouseCoopers for his work in this area. His research has also won the John Little Best Paper Award (2008) and the INFORMS Society for Marketing Science Practice Prize Award (2007). Professor Kannan's research has also been selected as a finalist for the Paul Green Award (2008).
Funding Information:
The work presented in this paper was supported in part by The Petroleum Institute (PI) , Abu Dhabi, United Arab Emirates, as part of the Education and Energy Research Collaboration (EERC) agreement between the PI and University of Maryland, College Park. Such support does not constitute an endorsement by the funding agency of the opinions expressed in the paper. The authors would like to thank Philippe Kamaha for an earlier development of the model in the case study.
PY - 2012/2
Y1 - 2012/2
N2 - It is generally very challenging for an oil refinery to make integrated decisions encompassing multiple functions based on a traditional Decision Support System (DSS), given the complexity and interactions of various decisions. To overcome this limitation, we propose an integrated DSS framework by combining both business and engineering systems with a dashboard. The dashboard serves as a human-computer interface and allows a decision maker to adjust decision variables and exchange information with the DSS. The proposed framework provides a two-stage decision making mechanism based on optimization and agent-based models. Under the proposed DSS, the decision maker decides on the values of a subset of decision variables. These values, or the first-stage decision, are forwarded through the dashboard to the DSS. For the given set of first-stage decision variables, a multi-objective robust optimization problem, based on an integrated business and engineering simulation model, is solved to obtain the values for a set of second-stage decision variables. The two-stage decision making process iterates until a convergence is achieved. A simple oil refinery case study with an example dashboard demonstrates the applicability of the integrated DSS.
AB - It is generally very challenging for an oil refinery to make integrated decisions encompassing multiple functions based on a traditional Decision Support System (DSS), given the complexity and interactions of various decisions. To overcome this limitation, we propose an integrated DSS framework by combining both business and engineering systems with a dashboard. The dashboard serves as a human-computer interface and allows a decision maker to adjust decision variables and exchange information with the DSS. The proposed framework provides a two-stage decision making mechanism based on optimization and agent-based models. Under the proposed DSS, the decision maker decides on the values of a subset of decision variables. These values, or the first-stage decision, are forwarded through the dashboard to the DSS. For the given set of first-stage decision variables, a multi-objective robust optimization problem, based on an integrated business and engineering simulation model, is solved to obtain the values for a set of second-stage decision variables. The two-stage decision making process iterates until a convergence is achieved. A simple oil refinery case study with an example dashboard demonstrates the applicability of the integrated DSS.
KW - Agent-based modeling
KW - Decision Support System (DSS)
KW - Knowledge management
KW - Non-linear optimization
KW - Oil markets
KW - Refinery
KW - Simulation
UR - https://www.scopus.com/pages/publications/84856022279
U2 - 10.1016/j.dss.2011.11.019
DO - 10.1016/j.dss.2011.11.019
M3 - Article
AN - SCOPUS:84856022279
SN - 0167-9236
VL - 52
SP - 729
EP - 741
JO - Decision Support Systems
JF - Decision Support Systems
IS - 3
ER -