docs.json

[
  {
    "title": "Introduction to Linear Operators",
    "repo": "introduction-to-linear-operators",
    "short": "Learn about LinearOperators.jl",
    "date": "2021-01-01",
    "tags": ["introduction", "linear-operators"],
    "pkgs": ["LinearOperators", "Krylov"]
  },
  {
    "title": "Creating a JSO-compliant solver",
    "repo": "creating-a-jso-compliant-solver",
    "short": "A thorough guide for developers, from 0 to benchmarking.",
    "date": "2021-01-01",
    "tags": ["solver", "benchmark"],
    "pkgs": ["ADNLPModels", "JSOSolvers", "NLPModels", "SolverBenchmark", "SolverCore"]
  },
  {
    "title": "How to solve an optimization problem with Ipopt and NLPModels",
    "repo": "solve-an-optimization-problem-with-ipopt",
    "short": "Quick guide to help you write your problem and solve it using Ipopt",
    "date": "2021-01-01",
    "tags": ["solve", "problem", "model", "short"],
    "pkgs": ["ADNLPModels", "NLPModelsIpopt"]
  },
  {
    "title": "How to create a model from the objective function and its derivatives",
    "repo": "create-a-manual-model",
    "short": "Write a simple model with total control over its derivatives.",
    "date": "2021-01-01",
    "tags": ["model", "logistic-regression", "manual", "comparison"],
    "pkgs": ["ADNLPModels", "JSOSolvers", "ManualNLPModels", "NLPModels", "NLPModelsJuMP"]
  },
  {
    "title": "Solve a PDE-constrained optimization problem",
    "repo": "solve-pdenlpmodels-with-jsosolvers",
    "short": "Solve a discretized PDE-constrained optimization problem using DCISolver and Ipopt.",
    "date": "2022-01-24",
    "tags": ["pde", "solve"],
    "pkgs": ["DCISolver", "JSOSolvers", "NLPModels", "NLPModelsIpopt", "NLPModelsModifiers", "PDENLPModels"]
  },
  {
    "title": "Introduction to QuadraticModels",
    "repo": "introduction-to-quadraticmodels",
    "short": "Learn about QuadraticModels.jl",
    "date": "2022-03-07",
    "tags": ["introduction", "model", "solver"],
    "pkgs": ["LinearOperators", "NLPModels", "NLPModelsModifiers", "QPSReader", "QuadraticModels", "RipQP", "SparseMatricesCOO"]
  },
  {
    "title": "Introduction to CUTEst",
    "repo": "introduction-to-cutest",
    "short": "CUTEst.jl was the first package in the JSO ecosystem. It is an essential part of the nonlinear optimization academic research landscape.",
    "date": "2022-03-15",
    "tags": ["introduction", "model", "test"],
    "pkgs": ["CUTEst", "Krylov", "NLPModels"]
  },
  {
    "title": "Introduction to BenchmarkProfiles",
    "repo": "introduction-to-benchmarkprofiles",
    "short": "This is a simple package to plot mathematical performance and data profiles, as defined by Elizabeth Dolan, Jorge Moré and Stefan Wild",
    "date": "2022-06-07",
    "tags": ["introduction", "benchmark"],
    "pkgs": ["BenchmarkProfiles"]
  },
  {
    "title": "Introduction to RipQP",
    "repo": "introduction-to-ripqp",
    "short": "A package to optimize linear and quadratic problems in QuadraticModel format using a regularized interior-point method.",
    "date": "2022-06-25",
    "tags": ["introduction", "quadratic", "regularized", "solver"],
    "pkgs": ["QuadraticModels", "LinearAlgebra", "SparseMatricesCOO", "RipQP", "QPSReader", "QuadraticModels", "DelimitedFiles", "MatrixMarket", "TimerOutputs"]
  }
]