We often celebrate optimization models for delivering an optimal solution, but as Warren B. Powell highlights in this Analytics Magazine article, real operations don’t happen just once, they evolve over time. The piece explores how traditional mixed-integer programming models fall short when decisions today influence tomorrow’s state, and why parameterized, sequential decision models may better reflect the complexity practitioners actually face.
For anyone working with MILPs, sequential decision processes, or real-world planning problems, this is a great read that challenges how we think about “optimality” in dynamic environments.
Read the full article here
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Garrett Johnston
Membership Engagement Coordinator
gjohnston@informs.org------------------------------