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_posts/2022-09-06-ant-colony-optimization-tsp.md

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@@ -87,7 +87,7 @@ That is, the probability of choosing a certain edge will be proportional to:
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Where P is the level of pheromones in that edge, and D the distance the edge covers. To get the distribution we sample from at each random jump, we normalize these weight coefficients so they add up to one.
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<div class="wide-eighty">
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{% raw %}<script src="https://gist.github.com/StrikingLoo/432302f114822d24504cf6bab0ab3964.js"></script>{% endraw %}
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{% raw %}<script defer src="https://gist.github.com/StrikingLoo/432302f114822d24504cf6bab0ab3964.js"></script>{% endraw %}
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</div>
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After that, the optimization procedure itself consists of:
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@@ -107,7 +107,7 @@ Additionally, I tried a few more modifications to the algorithm: the 'elite' or
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Here is the whole function in all its glory (with comments for sanity).
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<div class="wide-eighty">
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{% raw %}<script src="https://gist.github.com/StrikingLoo/778db2438b18d38f126082c046b19acd.js"></script>{% endraw %}
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{% raw %}<script defer src="https://gist.github.com/StrikingLoo/778db2438b18d38f126082c046b19acd.js"></script>{% endraw %}
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</div>
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Some possible improvements for this algorithm that I didn't have the time for:

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