Abstract
For a set of people and a set of items, with each person having a preference list that ranks all items from most wanted to least wanted, we consider the problem of matching every person with a unique item. A matching is called -popular if for any other matching , the number of people who prefer to is at most plus the number of those who prefer to . In 2006, Mahdian showed that when randomly generating people's preference lists, if , then a 0-popular matching exists with probability; and if , then a 0-popular matching exists with probability. The ratio 1.42 can be viewed as a transition point, at which the probability rises from asymptotically zero to asymptotically one, for the case . In this paper, we introduce an upper bound and a lower bound of the transition point in more general cases. In particular, we show that when randomly generating each person's preference list, if , then an -popular matching exists with probability (upper bound); and if , then an -popular matching exists with probability (lower bound).
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