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Add benchmark results for multidimensional knapsack
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@@ -139,7 +146,6 @@
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<li class="third-level"><a href="#problem-definition">Problem definition</a></li>
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<li class="third-level"><a href="#random-instance-generator">Random instance generator</a></li>
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<li class="third-level"><a href="#benchmark-challenges_1">Benchmark challenges</a></li>
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<li class="third-level"><a href="#benchmark-results">Benchmark results</a></li>
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<li class="second-level"><a href="#multidimensional-0-1-knapsack-problem">Multidimensional 0-1 Knapsack Problem</a></li>
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<li class="third-level"><a href="#problem-definition_1">Problem definition</a></li>
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fix_graph=True)
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</code></pre>
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<h3 id="benchmark-results">Benchmark results</h3>
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<h4 id="challenge-a_1">Challenge A</h4>
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<p><img alt="alt" src="../figures/benchmark_stab_a.png" /></p>
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<h2 id="multidimensional-0-1-knapsack-problem">Multidimensional 0-1 Knapsack Problem</h2>
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<h3 id="problem-definition_1">Problem definition</h3>
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@@ -225,7 +229,26 @@ from the provided probability distributions <code>K</code> and <code>u</code>.</
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<li>Freville, Arnaud, and Gérard Plateau. <em>An efficient preprocessing procedure for the multidimensional 0–1 knapsack problem.</em> Discrete applied mathematics 49.1-3 (1994): 189-212.</li>
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<li>Fréville, Arnaud. <em>The multidimensional 0–1 knapsack problem: An overview.</em> European Journal of Operational Research 155.1 (2004): 1-21.</li>
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</ul>
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</div></div>
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</div>
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<h4 id="challenge-a_1">Challenge A</h4>
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<ul>
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<li>250 variables, 10 constraints, fixed weights</li>
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<li>$w \sim U(0, 1000), \gamma \sim U(0.95, 1.05)$</li>
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<li>$K = 500, u \sim U(0, 1), \alpha = 0.25$</li>
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<li>500 training instances, 50 test instances</li>
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</ul>
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<pre><code class="python">MultiKnapsackGenerator(n=randint(low=250, high=251),
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m=randint(low=10, high=11),
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w=uniform(loc=0.0, scale=1000.0),
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K=uniform(loc=500.0, scale=0.0),
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u=uniform(loc=0.0, scale=1.0),
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alpha=uniform(loc=0.25, scale=0.0),
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fix_w=True,
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w_jitter=uniform(loc=0.95, scale=0.1),
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)
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</code></pre>
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<p><img alt="alt" src="../figures/benchmark_knapsack_a.png" /></p></div>
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</div>
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@@ -234,17 +257,17 @@ from the provided probability distributions <code>K</code> and <code>u</code>.</
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<hr>
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<p>
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<small>Copyright © 2020, UChicago Argonne, LLC. All Rights Reserved.</small><br>
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<small>Copyright © 2020, UChicago Argonne, LLC. All Rights Reserved.<br></small>
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<small>Documentation built with <a href="http://www.mkdocs.org/">MkDocs</a>.</small>
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@@ -256,11 +279,8 @@ from the provided probability distributions <code>K</code> and <code>u</code>.</
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