Greedy Solutions for General Set Covering Problems
Set covering problems are well known as hard . Therefore only small problems can be solved effectively by standard methods of integer programming. The solution of larger problems requires the use of methods with polynomial time behaviour. Thus the choice of methods is restricted to heuristics, which can eventually be combined in the framework of branch-and-bound to give ‘hybrid’ algorithms. In  Balas and Ho report on an algorithm of this type, based on several heuristics, subgradient optimization, cutting planes, and implicit enumeration.
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