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<!doctype html> <html lang=en class=has-navbar-fixed-top > <meta charset=UTF-8 > <meta name=viewport content="width=device-width, initial-scale=1"> <link rel=stylesheet href="/css/styles.css"> <style> html {font-size: 17px;} .franklin-content {position: relative; padding-left: 8%; padding-right: 5%; line-height: 1.35em;} @media (min-width: 940px) { .franklin-content {width: 100%; margin-left: auto; margin-right: auto;} } @media (max-width: 768px) { .franklin-content {padding-left: 6%; padding-right: 6%;} } </style> <link rel=icon href="/assets/favicon.png"> <title>Julia Smooth Optimizers @ JuliaCon Local Eindhoven 2023</title> <script src="/libs/highlight/highlight.pack.js"></script> <script src="https://unpkg.com/clipboard@2/dist/clipboard.min.js"></script> <script type=module src="https://unpkg.com/[email protected]/dist/ionicons/ionicons.esm.js"></script> <script nomodule src="https://unpkg.com/[email protected]/dist/ionicons/ionicons.js"></script> <script> hljs.getLanguage('julia').keywords.custom = 'obj grad hess AbstractNLPModel'; </script> <nav class="navbar is-primary is-fixed-top" role=navigation aria-label="main navigation"> <div class=navbar-brand > <a class=navbar-item href=""> <img src="/assets/jso.png"> </a> <a role=button class=navbar-burger aria-label=menu aria-expanded=false data-target=navbarBasicExample > <span aria-hidden=true ></span> <span aria-hidden=true ></span> <span aria-hidden=true ></span> </a> </div> <div id=navbarBasicExample class=navbar-menu > <div class=navbar-start > <a class=navbar-item href="/"> Home </a> <a class=navbar-item href="/news-and-blogposts/"> News and Blogposts </a> <a class=navbar-item href="/tutorials/"> Tutorials </a> <div class="navbar-item has-dropdown is-hoverable"> <a class=navbar-link href="/ecosystems/index.html"> Ecosystems </a> <div class=navbar-dropdown > <a class=navbar-item href="/ecosystems/linear-algebra/"> Linear Algebra </a> <a class=navbar-item href="/ecosystems/models/"> Models </a> <a class=navbar-item href="/ecosystems/solvers/"> Solvers </a> </div> </div> <a class=navbar-item href="/references/"> References </a> <a class=navbar-item href="/contributing/"> Contributing </a> </div> <div class=navbar-end > <a class="navbar-item icon-text" href="https://github.com/JuliaSmoothOptimizers/juliasmoothoptimizers.github.io/issues"> <span class=icon > <ion-icon size=large name=logo-github ></ion-icon> </span> <span>Report an issue</span> </a> </div> </div> </nav> <section class=section > <div class=container > <div class=content > <div class=franklin-content ><h2 id=exploring_nonlinear_optimization_with_juliasmoothoptimizers_at_juliacon_local_eindhoven_2023 ><a href="#exploring_nonlinear_optimization_with_juliasmoothoptimizers_at_juliacon_local_eindhoven_2023" class=header-anchor >Exploring Nonlinear Optimization with JuliaSmoothOptimizers at JuliaCon Local Eindhoven 2023</a></h2> <p>We are excited to share that one of the core members of the JuliaSmoothOptimizers organization, <a href="https://abelsiqueira.com/">Abel Siqueira</a>, recently delivered a compelling talk at the <a href="https://juliacon.org/local/eindhoven2023/">JuliaCon Local Eindhoven 2023</a> conference in the Netherlands. The conference, co-located with PyData Eindhoven 2023, provided an excellent platform for discussions and presentations on the latest developments in Julia and related technologies. As published <a href="https://jso.dev/news-and-blogposts/2023/2023-09-06-jso-community-partner-juliacon-eindhoven/">in a previous post</a>, Julia Smooth Optimizers was a community partner of the event.</p> <p><a href="https://juliacon.org/local/eindhoven2023/"><img src="/assets/julia-packages-in-region.png" alt="JuliaCon Local Eindhoven 2023" /></a></p> <p>Abel Siqueira&#39;s talk, titled <a href="https://eindhoven2023.pydata.org/juliacon/talk/MYXETU/"><em>Nonlinear Optimization with the Julia Smooth Optimizers Packages</em></a>, delved into the rich ecosystem built by the JSO since its inception in 2015. With over 50 registered packages covering a wide range of nonlinear optimization and linear algebra topics, JSO has been a driving force in providing researchers with the necessary tools to seamlessly transition from prototyping to publication-ready code.</p> <p>With an extensive package ecosystem and the introduction of JSOSuite, the organization continues to play a pivotal role in bridging the gap between research and practical, user-friendly solutions. As we look forward to the future, events like JuliaCon Local Eindhoven contribute significantly to the collaborative and innovative spirit of the Julia community.</p> <p>Abstract: <em>The talk highlighted JSO&#39;s primary objective: to empower researchers by offering high-level, well-maintained optimization packages. The organization is committed to facilitating a smooth journey from the conceptualization of ideas to the development of user-friendly optimization packages. A significant stride in this direction is the introduction of JSOSuite, a comprehensive package aiming to be a one-stop solution for nonlinear optimization in Julia.</em></p> <p>You can check the full talk at <a href="https://www.youtube.com/watch?v&#61;i1eeD3uHbZ4">The Julia Programming Language Youtube</a>.</p> <p><a href="https://twitter.com/eScienceCenter/status/1731659629287862537"><img src="/assets/abel-juliacon-local-24.png" alt="Some tweets about the event" /></a></p> </div> </div> </div> </div> </section> <footer class=footer > <div class="content has-text-centered is-small"> &copy; Abel Soares Siqueira. <br> <a class=link href="https://github.com/JuliaSmoothOptimizers/">JSO at GitHub</a> </div> </footer>
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<!doctype html> <html lang=en class=has-navbar-fixed-top > <meta charset=UTF-8 > <meta name=viewport content="width=device-width, initial-scale=1"> <link rel=stylesheet href="/css/styles.css"> <style> html {font-size: 17px;} .franklin-content {position: relative; padding-left: 8%; padding-right: 5%; line-height: 1.35em;} @media (min-width: 940px) { .franklin-content {width: 100%; margin-left: auto; margin-right: auto;} } @media (max-width: 768px) { .franklin-content {padding-left: 6%; padding-right: 6%;} } </style> <link rel=icon href="/assets/favicon.png"> <title>Julia Smooth Optimizers @ JuliaCon Local Eindhoven 2023</title> <script src="/libs/highlight/highlight.pack.js"></script> <script src="https://unpkg.com/clipboard@2/dist/clipboard.min.js"></script> <script type=module src="https://unpkg.com/[email protected]/dist/ionicons/ionicons.esm.js"></script> <script nomodule src="https://unpkg.com/[email protected]/dist/ionicons/ionicons.js"></script> <script> hljs.getLanguage('julia').keywords.custom = 'obj grad hess AbstractNLPModel'; </script> <nav class="navbar is-primary is-fixed-top" role=navigation aria-label="main navigation"> <div class=navbar-brand > <a class=navbar-item href=""> <img src="/assets/jso.png"> </a> <a role=button class=navbar-burger aria-label=menu aria-expanded=false data-target=navbarBasicExample > <span aria-hidden=true ></span> <span aria-hidden=true ></span> <span aria-hidden=true ></span> </a> </div> <div id=navbarBasicExample class=navbar-menu > <div class=navbar-start > <a class=navbar-item href="/"> Home </a> <a class=navbar-item href="/news-and-blogposts/"> News and Blogposts </a> <a class=navbar-item href="/tutorials/"> Tutorials </a> <div class="navbar-item has-dropdown is-hoverable"> <a class=navbar-link href="/ecosystems/index.html"> Ecosystems </a> <div class=navbar-dropdown > <a class=navbar-item href="/ecosystems/linear-algebra/"> Linear Algebra </a> <a class=navbar-item href="/ecosystems/models/"> Models </a> <a class=navbar-item href="/ecosystems/solvers/"> Solvers </a> </div> </div> <a class=navbar-item href="/references/"> References </a> <a class=navbar-item href="/contributing/"> Contributing </a> </div> <div class=navbar-end > <a class="navbar-item icon-text" href="https://github.com/JuliaSmoothOptimizers/juliasmoothoptimizers.github.io/issues"> <span class=icon > <ion-icon size=large name=logo-github ></ion-icon> </span> <span>Report an issue</span> </a> </div> </div> </nav> <section class=section > <div class=container > <div class=content > <div class=franklin-content ><h2 id=exploring_nonlinear_optimization_with_juliasmoothoptimizers_at_juliacon_local_eindhoven_2023 ><a href="#exploring_nonlinear_optimization_with_juliasmoothoptimizers_at_juliacon_local_eindhoven_2023" class=header-anchor >Exploring Nonlinear Optimization with JuliaSmoothOptimizers at JuliaCon Local Eindhoven 2023</a></h2> <p>We are excited to share that one of the core members of the JuliaSmoothOptimizers organization, <a href="https://abelsiqueira.com/">Abel Siqueira</a>, recently delivered a compelling talk at the <a href="https://juliacon.org/local/eindhoven2023/">JuliaCon Local Eindhoven 2023</a> conference in the Netherlands. The conference, co-located with PyData Eindhoven 2023, provided an excellent platform for discussions and presentations on the latest developments in Julia and related technologies. As published <a href="https://jso.dev/news-and-blogposts/2023/2023-09-06-jso-community-partner-juliacon-eindhoven/">in a previous post</a>, Julia Smooth Optimizers was a community partner of the event.</p> <p><a href="https://juliacon.org/local/eindhoven2023/"><img src="/assets/julia-packages-in-region.png" alt="JuliaCon Local Eindhoven 2023" /></a></p> <p>Abel Siqueira&#39;s talk, titled <a href="https://www.youtube.com/watch?v&#61;i1eeD3uHbZ4"><em>Nonlinear Optimization with the Julia Smooth Optimizers Packages</em></a>, delved into the rich ecosystem built by the JSO since its inception in 2015. With over 50 registered packages covering a wide range of nonlinear optimization and linear algebra topics, JSO has been a driving force in providing researchers with the necessary tools to seamlessly transition from prototyping to publication-ready code.</p> <p>With an extensive package ecosystem and the introduction of JSOSuite, the organization continues to play a pivotal role in bridging the gap between research and practical, user-friendly solutions. As we look forward to the future, events like JuliaCon Local Eindhoven contribute significantly to the collaborative and innovative spirit of the Julia community.</p> <p>Abstract: <em>The talk highlighted JSO&#39;s primary objective: to empower researchers by offering high-level, well-maintained optimization packages. The organization is committed to facilitating a smooth journey from the conceptualization of ideas to the development of user-friendly optimization packages. A significant stride in this direction is the introduction of JSOSuite, a comprehensive package aiming to be a one-stop solution for nonlinear optimization in Julia.</em></p> <p>You can check the full talk at <a href="https://www.youtube.com/watch?v&#61;i1eeD3uHbZ4">The Julia Programming Language Youtube</a>.</p> <p><a href="https://x.com/eScienceCenter/status/1731659629287862537"><img src="/assets/abel-juliacon-local-24.png" alt="Some tweets about the event" /></a></p> </div> </div> </div> </div> </section> <footer class=footer > <div class="content has-text-centered is-small"> &copy; Abel Soares Siqueira. <br> <a class=link href="https://github.com/JuliaSmoothOptimizers/">JSO at GitHub</a> </div> </footer>

β€Žtutorials/introduction-to-pdenlpmodels/index.htmlβ€Ž

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<pre><code class=language-plaintext >4.465311648679671e-7</code></pre>
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<p>We will use the solution found to initialize our solvers.</p>
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<h2 id=solve_the_problem ><a href="#solve_the_problem" class=header-anchor >Solve the Problem</a></h2>
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<p>Finally, we are ready to solve the PDE-constrained optimization problem with a targeted tolerance of <code>10⁻⁡</code>. In the following, we will use both Ipopt and DCI on our problem. We refer to the tutorial <a href="https://jso-docs.github.io/solve-an-optimization-problem-with-ipopt/">How to solve a small optimization problem with Ipopt &#43; NLPModels</a> for more information on <code>NLPModelsIpopt</code>.</p>
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<p>Finally, we are ready to solve the PDE-constrained optimization problem with a targeted tolerance of <code>10⁻⁡</code>. In the following, we will use both Ipopt and DCI on our problem. We refer to the tutorial <a href="https://jso.dev/tutorials/solve-an-optimization-problem-with-ipopt/">How to solve a small optimization problem with Ipopt &#43; NLPModels</a> for more information on <code>NLPModelsIpopt</code>.</p>
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<pre><code class=language-julia >using NLPModelsIpopt
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# Set &#96;print_level &#61; 0&#96; to avoid printing detailed iteration information.

β€Žtutorials/introduction-to-ripqp/index.htmlβ€Ž

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psoperations: βˆ…
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relative_iter_cnt: 20</code></pre> <p>The <code>stats</code> output is a <a href="https://jso.dev/SolverCore.jl/dev/reference/#SolverCore.GenericExecutionStats">GenericExecutionStats</a>.</p> <p>It is also possible to use the package <a href="https://github.com/JuliaSmoothOptimizers/QPSReader.jl">QPSReader.jl</a> in order to read convex quadratic problems in MPS or SIF formats: &#40;download <a href="https://raw.githubusercontent.com/JuliaSmoothOptimizers/RipQP.jl/main/test/QAFIRO.SIF">QAFIRO</a>&#41;</p> <pre><code class=language-julia >using QPSReader, QuadraticModels
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relative_iter_cnt: 20</code></pre> <p>The <code>stats</code> output is a <a href="https://jso.dev/SolverCore.jl/dev/">GenericExecutionStats</a>.</p> <p>It is also possible to use the package <a href="https://github.com/JuliaSmoothOptimizers/QPSReader.jl">QPSReader.jl</a> in order to read convex quadratic problems in MPS or SIF formats: &#40;download <a href="https://raw.githubusercontent.com/JuliaSmoothOptimizers/RipQP.jl/main/test/QAFIRO.SIF">QAFIRO</a>&#41;</p> <pre><code class=language-julia >using QPSReader, QuadraticModels
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QM &#61; QuadraticModel&#40;readqps&#40;&quot;assets/QAFIRO.SIF&quot;&#41;&#41;</code></pre> <pre><code class=language-plaintext >QuadraticModels.QuadraticModel&#123;Float64, Vector&#123;Float64&#125;, SparseMatricesCOO.SparseMatrixCOO&#123;Float64, Int64&#125;, SparseMatricesCOO.SparseMatrixCOO&#123;Float64, Int64&#125;&#125;
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Problem name: Generic
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All variables: β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ 32 All constraints: β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ 27

β€Žtutorials/introduction-to-solverbenchmark/index.htmlβ€Ž

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β”‚ prob009 β”‚ -9.292e-01 β”‚ 2m 28s 248989ΞΌs β”‚
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β”‚ prob010 β”‚ &#43;7.889e-02 β”‚ 3m 50s 955096ΞΌs β”‚
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β””β”€β”€β”€β”€β”€β”€β”€β”€β”€β”΄β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”΄β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜</code></pre>
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<p>See the <a href="https://ronisbr.github.io/PrettyTables.jl/stable/man/formatters/">PrettyTables.jl documentation</a> for more information.</p>
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<p>See the <a href="https://ronisbr.github.io/PrettyTables.jl/stable/">PrettyTables.jl documentation</a> for more information.</p>
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<p>When using LaTeX format, the output must be understood by LaTeX. By default, numerical data in the table is wrapped in inline math environments. But those math environments would interfere with our formatting of the time. Thus we must first disable them for the <code>time</code> column using <code>col_formatters</code>, and then apply the PrettyTables formatter as above:</p>
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<pre><code class=language-julia >fmt_override &#61; Dict&#40;:f &#61;&gt; &quot;&#37;&#43;10.3e&quot;,
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:t &#61;&gt; &quot;&#37;08.2f&quot;&#41;

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