In this paper we exploit concepts from Information Theory to improve the classical Chvatal greedy algorithm for set covering problem. particular, develop a new procedure, called Surprisal-Based Greedy Heuristic (SBH), incorporating computation of “surprisal” measure when selecting solution columns. Computational experiments, performed on instances OR-Library, showed that SBH yields 2.5% improve...