Abstract
To overcome the shortcoming of ordinary genetic algorithm, an immune genetic algorithm is designed to better solve the job shop scheduling. Based on the characteristic that optimal offspring of each generation corresponding to the workpiece machining order is favorable to the target function, the algorithm abstracts vaccine and employs the improved elitist-crossover strategy and the simulated-annealing-based vaccine selection method. The simulation tests have showed the validity and practicability of the algorithm, and that the algorithm has better convergence speed and optimization accuracy. Specially, as a result of the algorithm, the prematurity which is a common phenomenon in the ordinary genetic algorithm, is efficiently avoided.
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