Wednesday, August 31, 2011

Nagurney Presents at Montreal Conference

Ladimer S. Nagurney, associate professor of electrical, computer, and biomedical engineering, CETA, was coauthor of a paper, "Medical Nuclear Supply Chain Design: A Tractable Network Model and Computational Approach," presented at the Seventh Conference on Integrated Risk Management in Operations and Global Supply Chains at McGill University, Montreal, Canada, July 31-August 1, 2011.

The conference, co-sponsored by McGill University, the Management Science Research Center at the Desautels Faculty of Management, the Group for Research in Decision Analysis (GERAD), a multi-university research center located in Montreal, and the Boeing Center on Technology, Information and Manufacturing (BCTIM) at Washington University in St. Louis, was intended to facilitate and stimulate interactions and knowledge sharing on important issues of risk management in global supply chains. The conference extended beyond stimulating research presentations to constructively challenge current practices and research paradigms, and, with a single track, offered the opportunity for productive interactions among speakers and conference participants.

The paper, coauthored with Anna Nagurney of the University of Massachusetts Amherst, develops a tractable network model and computational approach for the design and redesign of medical nuclear supply chains focusing on the supply chain of the most commonly used radioisotope for medical imaging utilized in cardiac and cancer diagnostics. The generalized network model, which derives formulae for the arc and path multipliers that capture the underlying physics of radioisotope decay, is a multiple criteria system-optimization model that includes total cost minimization, the minimization of cost associated with nuclear waste discarding, and also risk management, coupled with investment (or disinvestment) costs. Its solution yields the optimal link investments as well as the optimal product flows so that demand at the medical facilities is satisfied. It's framework provides the foundation for further empirical research and the basis for the modeling and analysis of supply chain networks for other very time-sensitive medical products.

See a copy of the presentation.


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