To solve the double-objective optimal of dual resource constrained job shop scheduling problem, an inherited
genetic algorithm is proposed, in which the evolutionary experience of parent population is inherited by the means of branch population generation with pheromones to accelerate the convergence rate. Meanwhile, by using the four-dimensional chromosome coding method, based on comparison among time windows, the activable decoding algorithm is utilized with reference to the character of dual resource constrained to improve the overall searching ability. During the evolution process, the championship selection strategy based on Pareto index weakens the impact of the Pareto level of chromosomes obviously to keep the community diversity. The reliable convergence of algorithm is guaranteed by using elitist preservation strategy. The simulation experiment and statistical analysis on extant and random example show that the proposed method has good performance.