Solution Provided by Gurobi violates Model Constraints

Solomon Joseph

2019年12月04日 12:11 編集済み

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I am currently using the Gurobi Optimizer to create an ILP formulation for a variation of the Metric TSP problem. However, the solution returned by the Gurobi Optimizer violates constraints that I have included in the model. I have variables for the edges, named e, and vertices, named v, in the graph, and I have included the constraint that e.sum() >= v.sum(). However, the solution that is being provided by the Optimizer completely violates this constraint. Am I not properly adding this constraint to the ILP formulation? I am using model.addVars() for each of my variables, with model.addConstrs(). I have also added a couple of lazy constraints, so I have set model.params.LazyConstraints to 1. Thanks for any and all help!

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  Simranjit Kaur

  • Gurobi Staff

  2025年06月23日 03:20 編集済み

  This post is more than three years old. Some information may not be up to date. For current information, please check the Gurobi Documentation or Knowledge Base. If you need more help, please create a new post in the community forum. Or why not try our AI Gurobot?.
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  Alicia Buhk

  2019年12月04日 19:52

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  Maybe you could provide your model formulation?

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