Dartmouth Research Cited as Key to Meeting Engineering "Grand Challenges"

Dartmouth engineering professor Vikrant Vaze was cited in a report invited by the National Science Foundation (NSF) last year, and recently made available, to study the connection between the field of operations research (OR) and meeting the nation's "Grand Challenges for Engineering."

“OR has evolved through the convergence of computational, mathematical, and economic sciences for design and analysis of complex socio-technical systems," says Professor Vaze. "For solving the ‘Grand Challenges’ associated with these systems, such as transportation, healthcare and energy, it is critical to develop not only new technology but also better ways of modeling the behavior of humans managing the technology. The latter is especially important because what is best for an individual, or a group of individuals, may sometimes be far from the best for the society as a whole.”

The report submitted to NSF states: “OR has long played a role in optimizing dynamic prices in systems with many customers or stakeholders, such as in revenue management or congestion pricing. In systems with fewer stakeholders, some receiving relatively large portions of the available resources (such as in the case of airlines utilizing capacity in an air transportation system), additional complexities arise. In such systems, the formulation and analysis of effective policies is complicated by gaming behavior by the stakeholders, whereby they might provide untruthful or strategic information to advance their own interests. The challenge—which is significant—is to recognize this behavior and to adjust policies accordingly. While significant challenges persist, operations researchers, such as Vaze and Barnhart (2012), have begun to develop and apply game-theoretic, operations research-based approaches to optimize equity-efficiency trade-offs in such constrained resource systems with fewer stakeholders.”

"For the example of airlines," explains Vaze, "we've used game theory and operations research models—armed with knowledge of airline' decision making process under competition—to provide concrete and practical ways of drastically reducing the problem of airport congestion and flight delays at many of our major airports.

"Our results clearly show that incentivizing airlines to reduce the number of flights during the most congested times—many will sell a 9:00am flight to compete for passengers, even though the probability of that flight actually taking off at 9:00am is very low—results in a significant overall benefit to both airlines and passengers. By compromising their choices of flight times by an average of only 2 minutes, passengers would experience up to 40% fewer delays. Airlines, meanwhile, would fly fewer flights during the most congested times and reap an average of 20% increase in profit. It's a win-win.

"Overall, OR models help in understanding human decision-making and in creating incentives for the individuals to take actions that will benefit them and the society at the same time. This has been, and continues to be, a major contribution of OR to solving the 'Grand Challenges for Engineering.'”