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1809. Matrix-friendly modeling with gurobipy
Invited abstract in session TD-30: Python Modeling Tools, stream Software for Optimization.
Tuesday, 14:30-16:00Room: 064 (building: 208)
Authors (first author is the speaker)
| 1. | Robert Luce
|
| Gurobi |
Abstract
Gurobipy makes it very easy to build optimization models that are naturally
formulated with multi-dimensional constraints. In particular you can use
familiar concepts from NumPy like dimensions, shape, vectorization and
broadcasting in combination with gurobipy's matrix-friendly objects to
construct your optimization model. In this talk we will walk you through
the functionality, discuss performance aspects, and present best practice
code patterns.
Keywords
- Modeling Systems and Languages
Status: accepted
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