From 94bc7bc38e5ebd3a56e905e17b102c2cfcdf015d Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Beno=C3=AEt=20Legat?= Date: Thu, 7 Dec 2023 13:18:39 +0100 Subject: [PATCH] Fixes --- docs/src/tutorials/Polynomial Optimization/bilinear.jl | 2 +- docs/src/tutorials/Polynomial Optimization/ellipsoid.jl | 2 +- docs/src/tutorials/Polynomial Optimization/goldstein_price.jl | 2 +- docs/src/tutorials/Polynomial Optimization/min_univariate.jl | 2 +- docs/src/tutorials/Polynomial Optimization/qp.jl | 2 +- 5 files changed, 5 insertions(+), 5 deletions(-) diff --git a/docs/src/tutorials/Polynomial Optimization/bilinear.jl b/docs/src/tutorials/Polynomial Optimization/bilinear.jl index 8c2dc8249..6ee1f7204 100644 --- a/docs/src/tutorials/Polynomial Optimization/bilinear.jl +++ b/docs/src/tutorials/Polynomial Optimization/bilinear.jl @@ -6,7 +6,7 @@ # ## Introduction -# Consider the polynomial optimization problem from [Floudas1999, Section 3.1](@cite). +# Consider the polynomial optimization problem from [Floudas1999; Section 3.1](@cite). using Test #src using DynamicPolynomials diff --git a/docs/src/tutorials/Polynomial Optimization/ellipsoid.jl b/docs/src/tutorials/Polynomial Optimization/ellipsoid.jl index 295389f49..f91872087 100644 --- a/docs/src/tutorials/Polynomial Optimization/ellipsoid.jl +++ b/docs/src/tutorials/Polynomial Optimization/ellipsoid.jl @@ -6,7 +6,7 @@ # ## Introduction -# Consider the polynomial optimization problem from [Floudas1999, Section 3.5](@cite) +# Consider the polynomial optimization problem from [Floudas1999; Section 3.5](@cite) A = [ 0 0 1 diff --git a/docs/src/tutorials/Polynomial Optimization/goldstein_price.jl b/docs/src/tutorials/Polynomial Optimization/goldstein_price.jl index a0e45dbe8..f4b0a7c4f 100644 --- a/docs/src/tutorials/Polynomial Optimization/goldstein_price.jl +++ b/docs/src/tutorials/Polynomial Optimization/goldstein_price.jl @@ -47,7 +47,7 @@ solution_summary(model) # The moment matrix is as follows, we can already see the global minimizer # `[0, -1]` from the entries `(2, 1)` and `(3, 1)`. # This heuristic way to obtain solutions to the polynomial optimization problem -# is suggested in [Laurent2008, (6.15)](@cite). +# is suggested in [Laurent2008; (6.15)](@cite). ν = moment_matrix(con_ref) diff --git a/docs/src/tutorials/Polynomial Optimization/min_univariate.jl b/docs/src/tutorials/Polynomial Optimization/min_univariate.jl index 652407338..3bf6fef4d 100644 --- a/docs/src/tutorials/Polynomial Optimization/min_univariate.jl +++ b/docs/src/tutorials/Polynomial Optimization/min_univariate.jl @@ -6,7 +6,7 @@ # ## Introduction -# Consider the polynomial optimization problem from [Floudas1999, Section 4.10](@cite) +# Consider the polynomial optimization problem from [Floudas1999; Section 4.10](@cite) # of minimizing the linear function $-x_1 - x_2$ # over the basic semialgebraic set defined by the inequalities # $x_2 \le 2x_1^4 - 8x_1^3 + 8x_1^2 + 2$, diff --git a/docs/src/tutorials/Polynomial Optimization/qp.jl b/docs/src/tutorials/Polynomial Optimization/qp.jl index 73fd784bf..f0154d5fa 100644 --- a/docs/src/tutorials/Polynomial Optimization/qp.jl +++ b/docs/src/tutorials/Polynomial Optimization/qp.jl @@ -6,7 +6,7 @@ # ## Introduction -# Consider the nonconvex Quadratic Program (QP) from [Floudas1999, Section 2.2](@cite) +# Consider the nonconvex Quadratic Program (QP) from [Floudas1999; Section 2.2](@cite) # that minimizes the *concave* function $c^\top x - x^\top Qx / 2$ # over the polyhedron obtained by intersecting the hypercube $[0, 1]^5$ # with the halfspace $10x_1 + 12x_2 + 11x_3 + 7x_4 + 4x_5 \le 40$.