ampl-book/prod.ipynb

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    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "# Book Example: prod\n",
        "[![prod.ipynb](https://img.shields.io/badge/github-%23121011.svg?logo=github)](https://github.com/ampl/colab.ampl.com/blob/master/ampl-book/prod.ipynb) [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/ampl/colab.ampl.com/blob/master/ampl-book/prod.ipynb) [![Kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://github.com/ampl/colab.ampl.com/blob/master/ampl-book/prod.ipynb) [![Gradient](https://assets.paperspace.io/img/gradient-badge.svg)](https://console.paperspace.com/github/ampl/colab.ampl.com/blob/master/ampl-book/prod.ipynb) [![Open In SageMaker Studio Lab](https://studiolab.sagemaker.aws/studiolab.svg)](https://studiolab.sagemaker.aws/import/github/ampl/colab.ampl.com/blob/master/ampl-book/prod.ipynb) [![Hits](https://h.ampl.com/https://github.com/ampl/colab.ampl.com/blob/master/ampl-book/prod.ipynb)](https://colab.ampl.com)\n",
        "\n",
        "Description: book example autogenerated using prod.mod, prod.dat, and prod.run\n",
        "\n",
        "Tags: ampl-only, ampl-book\n",
        "\n",
        "Notebook author: N/A\n",
        "\n",
        "Model author: N/A\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {},
      "outputs": [],
      "source": [
        "# Install dependencies\n",
        "%pip install -q amplpy"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {},
      "outputs": [],
      "source": [
        "# Google Colab & Kaggle integration\n",
        "from amplpy import AMPL, ampl_notebook\n",
        "\n",
        "ampl = ampl_notebook(\n",
        "    modules=[\"coin\"],  # modules to install\n",
        "    license_uuid=\"default\",  # license to use\n",
        ")  # instantiate AMPL object and register magics"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "### Example: prod\n",
        "autogenerated using prod.mod, prod.dat, and prod.run"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {},
      "outputs": [],
      "source": [
        "%%writefile prod.mod\n",
        "set P;\n",
        "\n",
        "param a {j in P};\n",
        "param b;\n",
        "param c {j in P};\n",
        "param u {j in P};\n",
        "\n",
        "var X {j in P};\n",
        "\n",
        "maximize Total_Profit: sum {j in P} c[j] * X[j];\n",
        "\n",
        "subject to Time: sum {j in P} (1/a[j]) * X[j] <= b;\n",
        "\n",
        "subject to Limit {j in P}: 0 <= X[j] <= u[j];\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {},
      "outputs": [],
      "source": [
        "%%writefile prod.dat\n",
        "data;\n",
        "\n",
        "set P := bands coils;\n",
        "\n",
        "param:     a     c     u  :=\n",
        "  bands   200   25   6000\n",
        "  coils   140   30   4000 ;\n",
        "\n",
        "param b := 40;\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {},
      "outputs": [],
      "source": [
        "%%ampl_eval\n",
        "model prod.mod;\n",
        "data prod.dat;\n",
        "option solver cbc;\n",
        "solve;\n",
        "display X;\n"
      ]
    }
  ],
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      "file_extension": ".py",
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