Yirang Park

Negative number of continuous variables in the results

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## Summary Ran pyomo solve to optimize a model with one set of binary variables, using gurobi. The optimization was fine, but print(results) showed negative 'number of continuous variables' ###...

Performance issue with large number of variables

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Execution time is long for large number of variables in converting to ToQUBO models. The JuMP model: ``` A JuMP Model ├ solver: none ├ objective_sense: MIN_SENSE │ └ objective_function_type:...

https://github.com/JuliaQUBO/QUBOTools.jl/blob/46493c498b70e94f2fa49daf0e38a278fea33d09/src/library/format/qubin/parser.jl#L47C1-L47C48

ToQUBO.QUBOModel{Float64} ├ ObjectiveSense: MIN_SENSE ├ ObjectiveFunctionType: MOI.ScalarQuadraticFunction{Float64} ├ NumberOfVariables: 9941 └ NumberOfConstraints: 0 └ MOI.VariableIndex in MOI.ZeroOne: 0