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‎_sources/changelog.md.txt‎

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# Changelog
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## 0.5.1
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- Support llvmlite 0.45.0
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## 0.5.0
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- Overhaul of the nonlinear programming interface and now PyOptInterface can solve nonlinear programming problems with COPT, Gurobi and IPOPT.
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- Use `model.add_linear_constraint(x+y, (1.0, 2.0))` to add two-sided linear constraints

‎changelog.html‎

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<section class="tex2jax_ignore mathjax_ignore" id="changelog">
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<h1>Changelog<a class="headerlink" href="#changelog" title="Link to this heading"></a></h1>
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<h2>0.5.0<a class="headerlink" href="#id1" title="Link to this heading"></a></h2>
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<h2>0.5.0<a class="headerlink" href="#id2" title="Link to this heading"></a></h2>
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<li><p>Overhaul of the nonlinear programming interface and now PyOptInterface can solve nonlinear programming problems with COPT, Gurobi and IPOPT.</p></li>
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<li><p>Use <code class="docutils literal notranslate"><span class="pre">model.add_linear_constraint(x+y,</span> <span class="pre">(1.0,</span> <span class="pre">2.0))</span></code> to add two-sided linear constraints</p></li>
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<li><p>Add <code class="docutils literal notranslate"><span class="pre">poi.ScalarAffineFunction.from_numpy</span></code> to create scalar affine functions from numpy arrays quickly</p></li>
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<h2>0.4.1<a class="headerlink" href="#id3" title="Link to this heading"></a></h2>
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<li><p>Support writing solution files in HiGHS</p></li>
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<li><p>Add <code class="docutils literal notranslate"><span class="pre">model.close()</span></code> and <code class="docutils literal notranslate"><span class="pre">env.close()</span></code> methods to allow users release the license of commercial solvers manually</p></li>
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<li><p>Add <code class="docutils literal notranslate"><span class="pre">model.add_m_variables</span></code> and <code class="docutils literal notranslate"><span class="pre">model.add_m_linear_constraints</span></code> matrix modeling API</p></li>
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<li><p>Supports HiGHS 1.9.0 and Mosek 11</p></li>
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‎constraint.html‎

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No license found. Starting COPT with size limitations for non-commercial use
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‎container.html‎

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‎examples/economic_dispatch.html‎

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‎examples/optimal_control_rocket.html‎

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‎examples/optimal_power_flow.html‎

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@@ -566,16 +566,16 @@ <h2>Implementation<a class="headerlink" href="#implementation" title="Link to th
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15 1.7551955e+04 1.39e-05 6.19e-03 -3.8 1.78e-02 - 1.00e+00 9.72e-01f 1
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16 1.7551939e+04 1.54e-08 1.13e-06 -3.8 6.68e-04 - 1.00e+00 1.00e+00f 1
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17 1.7551891e+04 1.33e-08 1.02e-06 -5.7 9.92e-04 - 1.00e+00 1.00e+00f 1
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18 1.7551891e+04 1.14e-12 1.20e-10 -8.6 1.29e-05 - 1.00e+00 1.00e+00h 1
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18 1.7551891e+04 1.15e-12 1.20e-10 -8.6 1.29e-05 - 1.00e+00 1.00e+00h 1
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Number of Iterations....: 18
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(scaled) (unscaled)
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Objective...............: 4.3879727096482060e+02 1.7551890838592823e+04
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Dual infeasibility......: 1.1975398450658759e-10 4.7901593802635034e-09
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Constraint violation....: 1.1413092693146609e-12 1.1413092693146609e-12
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Complementarity.........: 2.5405436222389087e-09 1.0162174488955634e-07
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Overall NLP error.......: 2.5405436222389087e-09 1.0162174488955634e-07
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Objective...............: 4.3879727096482043e+02 1.7551890838592815e+04
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Dual infeasibility......: 1.1992717929842911e-10 4.7970871719371644e-09
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Constraint violation....: 1.1544099010052378e-12 1.1544099010052378e-12
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Complementarity.........: 2.5405436222207678e-09 1.0162174488883071e-07
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Overall NLP error.......: 2.5405436222207678e-09 1.0162174488883071e-07
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Number of objective function evaluations = 33
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Number of equality constraint Jacobian evaluations = 19
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Number of inequality constraint Jacobian evaluations = 19
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Number of Lagrangian Hessian evaluations = 18
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Total CPU secs in IPOPT (w/o function evaluations) = 0.007
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Total CPU secs in NLP function evaluations = 0.000
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Total CPU secs in IPOPT (w/o function evaluations) = 0.005
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Total CPU secs in NLP function evaluati
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</pre></div>
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</div>
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<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>ons = 0.000
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EXIT: Optimal Solution Found.
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</pre></div>
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Optimal active power output of the generators:
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Generator 0: 0.4
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Generator 1: 1.7
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Generator 2: 3.244984943109816
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Generator 2: 3.2449849431098117
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Generator 3: 0.0
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Generator 4: 4.7069359970171085
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Generator 4: 4.706935997017114
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</pre></div>
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