This paper studies a continual-domain ant colony algorithm based on the overlapping mutation operation, which forms a dynamic candidate group to the solution each component possible value, and records each possibility value information content in the candidate group．In each iteration of ant colony algorithm, firstly, it should choose the starting value of solution component according to the information content ,then use overlapping and variation operation to determine the overall optimal solution value. Through the corresponding algorithm design, regarding comes from the relative sufficiency big solution component value, its variation region is small, becomes the partial search, otherwise, the variation region is big, then constitutes the overall situation search. At the same time, along with iterative number of times increase, the component value variation scope changes gradually small, like this may enable the restraining process are many when the iterative number of times to be under the suitable control, accelerating convergence. Finally through the simulation experiment, compared the overlapping variation operation continual domain ant colony algorithm and the genetic algorithm performance，Conclusion had proven the overlapping variation operation continual domain ant colony algorithm had the high search superior solution ability, saved the computing time greatly.