Logistic Zones for Assignment
<p>Imagine this — You are a data-scientist working with one of the largest convenience delivery firms in the world. For the past few days, you have been working on a new algorithm that would speed up deliveries and cut costs! This algorithm is a new way of deciding which delivery-partner should be assigned to which order. This algorithm is good because it consumes inputs from several machine learning predictions. Predictions which have helped you account for all the potential variables — the customer’s expectations, the real-time traffic and the delivery-partner’s familiarity with the area.</p>
<p>You eagerly deploy this algorithm to test it out in a city. But it doesn’t work out. Why? Because it is simply too heavy. It simply takes too long to run! Orders keep piling up and delivery-partners keep waiting for their next duty — but the algorithm is just too slow! You can increase its speed by making it simple, removing a feature here, a tree there. But all that does is it turns your algo into a Random Forest Gump!</p>
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