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1University of Montreal, Canada; 2The University of Texas at Dallas; 3Cornell University
We introduce the problem of finding a student-optimal stable matching under adaptive priorities, i.e., when priorities depend on the assignment of other agents. We show that the problem is NP-hard, provide math-programming formulations for the problem, and introduce several heuristics to preprocess the instances and solve them. Finally, using both synthetic and real data from Chile, we show that clearinghouses can significantly improve students' welfare when considering dynamic priorities.
Matchmaking strategies for maximizing player engagement in video games
Xiao Lei1, Mingliu Chen2, Adam Elmachtoub2
1Unviersity of Hong Kong; 2Columbia University
TBD
Activated benders decomposition for day-ahead itinerary planning in paratransit
This research optimizes driver shifts and itineraries for paratransit operators, considering uncertainties like cancellations and no-shows. The SIPPAR model, using a shareability network representation and a two-stage stochastic optimization approach, reduces operating costs and improves robustness. The algorithm outperforms benchmarks in real-world instances, providing faster computational times and higher-quality solutions.
