TACIT: Optimization Models that Learn from Their Mistakes
Real-world optimization problems are difficult to model accurately because many objectives and constraints reside in domain experts'tacit knowledge, making them hard to formalize. As a result, optimization models often contain miscalibrated objectives, missing constraints, or omitted decision variables, leading to solu...
Maxime Bouscary, Marco Molinaro, Si-Rui Li et al.
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