PURPOSE: To obtain the satisfactory resolution of a large-scale problem at high speed by applying an genetic algorithm to a job shop scheduling problem.

CONSTITUTION: Probelm data and the parameter of the genetic algorithm are inputted from an input part 1. The resolution of the problem is expressed by an individual used for the genetic algorithm, and the evaluation of each individual is expressed by the maximum value (total work time) of a component for each individual. First of all, a random schedule constituting an initial individual group is generated by an initial individual group generation part 2. The individual groups are selected by a selection processing part 5, when an end condition is not satisfied, the individual groups are paired by two by two and impressed to a schedule calculation part 3 by a cross processing part 4, and any new individual and the evaluation value are obtained from the schedule calculation part 3. This processing is repeated to all the pairs of individuals in the individual group and returned to the processing of the selection processing part 5. The operations of respective parts are controlled by a control part 7.