Corporate dashboards for integrated business and engineering decisions in oil refineries: An agent-based approach

  • Authors:

  • W. Hu;A. Almansoori;P. K. Kannan;S. Azarm;Z. Wang

  • Affiliations:

  • Department of Mechanical Engineering, A. J. Clark School of Engineering, University of Maryland, College Park, MD, 20742, USA;Department of Chemical Engineering, The Petroleum Institute, P.O. Box 2533, Abu Dhabi, UAE;Department of Marketing, Robert H. Smith School of Business, University of Maryland, College Park, MD, 20742, USA;Department of Mechanical Engineering, A. J. Clark School of Engineering, University of Maryland, College Park, MD, 20742, USA;Department of Mechanical Engineering, A. J. Clark School of Engineering, University of Maryland, College Park, MD, 20742, USA

  • Venue:
  • Decision Support Systems
  • Year:
  • 2012

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Abstract

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.