On maximizing welfare when utility functions are subadditive

We consider the problem of maximizing welfare when allocating m items to n players with subadditive utility functions. Our main result is a way of rounding any fractional solution to a linear programming relaxation to this problem so as to give a feasible solution of welfare at least half that of the value of the fractional solution. This approximation ratio of 1/2 improves over an Ω(1/log m) ratio of Dobzinski, Nisan and Schapira STOC 2005. We also show an approximation ratio of 1 - 1/e when utility functions are fractionally subadditive. A result similar to this last result was previously obtained by Dobzinski and Schapira Soda 2006, but via a different rounding technique that requires the use of a so called "XOS oracle".The randomized rounding techniques that we use are oblivious in the sense that they only use the primal solution to the linear program relaxation, but have no access to the actual utility functions of the players. This allows us to suggest new incentive compatible mechanisms for combinatorial auctions, extending previous work of Lavi and Swamy FOCS 2005.