Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: The Reverse Greedy algorithm (RGREEDY) for the k-median problem works as follows. It starts by placing facilities on all nodes. At each step, it removes a facility to minimize the total distance to the remaining facilities. It stops when k facilities remain.  prove that, if the distance function is metric, then the approximation ratio of RGREEDY is beten Ω(log n/log log n) and O(log n).
['Marek Chrobak', 'Claire Kenyon', 'Neal E. Young']
I am writing a research paper on a idea The reverse greedy algorithm for the metric k -median problem
[{"from": "human", "value": "I am writing a research paper on a idea The reverse greedy algorithm for the metric k -median problem"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: The Reverse Greedy algorithm (RGREEDY) for the k-median problem works as follows. It starts by placing facilities on all nodes. At each step, it removes a facility to minimize the total distance to the remaining facilities. It stops when k facilities remain.  prove that, if the distance function is metric, then the approximation ratio of RGREEDY is beten \u03a9(log n/log log n) and O(log n)."}]