Minimal cost set covering using probabilistic methods

In this paper we address the problem of covering a set with elements from given subsets. Additionally, each such given subset has an associated coat, and the objective of the problem is to choose that set of subsets to cover the whole set, that would lead to minimal wat. This problem has got important practical counterpart in obtaining minimal expression of a boolean function in the domain of digital logic design. The probfem ia known to be NP-complete, and hence it ia almost impossible to determine the optimal solution for any large sized problems. The current paper investigates the performance of a couple of probabilistic techniques, namely, simulated annealing and genetic algorithms on the minimal cost set covering problem.