Job-shop scheduling problem(JSP) is one of the most difficulty combinatorial optimization problems. It is widely applied to productive management of enterprise. It is one of the most important links on CIMS. This paper proposed improved adaptive genetic algorithms for solving job-shop scheduling problems according to the idea that the best individual on current generation should be kept to next generation, but the best individual should be crossed and mutated by some probability. The software package for th...