This is a Julia package that implements sequantial quadratic programming algorithms for continuous nonlinear optimization.
]add SqpSolverConsider the following quadratic optimization problem
min x^2 + x
s.t. x^2 - x = 2
This problem can be solved by the following code snippet:
# Load packages
using SqpSolver, JuMP
using Ipopt # can be any QP solver
# Number of variables
n = 1
# Build nonlinear problem model via JuMP
model = Model(optimizer_with_attributes(
SqpSolver.Optimizer,
"external_optimizer" => Ipopt.Optimizer,
))
@variable(model, x)
@objective(model, Min, x^2 + x)
@NLconstraint(model, x^2 - x == 2)
# Solve optimization problem
JuMP.optimize!(model)
# Retrieve solution
Xsol = JuMP.value.(X)This material is based upon work supported by the U.S. Department of Energy, Office of Science, under contract number DE-AC02-06CH11357.