Like the N-convex algorithm, this algorithm attempts to find a set of candidates whose centroid is close to . The key difference is that instead of taking unique candidates, we allow candidates to populate the set multiple times. The result is that the weight of each candidate is simply given by its frequency in the list, which we can then index by random selection:
Less than 40 miles north of San Francisco, the city of Benicia has the quaint ambience of an American small town, where a white gazebo and sign for a community crab bake mark the approach to a vibrant downtown stretch of restaurants, cafes and antique shops.
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