A heuristic swarm intelligent optimization algorithm for coalitional resources games in virtual enterprises is proposed by comparing the similarity of coalitional resources games in virtual enterprises with the classic SAT problem. The algorithm fuses portions of the principles of Glowworm swarm optimization algorithm and Cuckoo Search optimization algorithm. It designs the feasible cross operator and the mutational operator, which can repair infeasible solution and maintain diversity. Experimental results indicate that the algorithm's iterations linearly increase with the stable coalitions ever found. Compared with the heuristic genetic algorithm, it performs better in hill-climbing performance and searching efficiency.