Uncovering expert objectives in production planning via inverse optimization: An industrial case study
Production planning in the manufacturing industry often relies on the use of optimization models, but defining an appropriate objective function can be a challenge. In practice, planners must balance competing goals, manage uncertainty, and account for qualitative business preferences that are difficult to quantify. As a result, many optimization models fail to match expert behavior, limiting trust and adoption. In this work, we propose a data-driven inverse optimization framework to infer the objective function implicitly captured in expert planners' decisions. We formulate the production planning problem as a mixed-integer linear program, where the unknown objective function is represen...
| Authors | Shivi Dixit, Rishabh Gupta, Adam Kelloway et al. |
|---|---|
| Primary category | math.OC |
| Published | 7 August 2026 |
| Last updated at source | 7 August 2026 |
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