Job Shop scheduling problem with continuous stochastic processing time

Due to the uncertainty in the practical scheduling problem, a stochastic Job Shop scheduling problem is proposed, in which the processing time is in normal distribution and the objective function is the expectation of the make span. Secondly, an intelligent optimization algorithm applied to this problem is promoted, it concludes three steps: obtaining the datum needed in the neural network through stochastic simulation, training the neural network through genetic algorithm, inserting the neural network into another genetic algorithm and applying the second genetic algorithm to Job Shop scheduling problem. Lastly, an example is given and it can prove that the intelligent optimization algorithm is effective.