Grey Chance Constrained Programming for Finite Intermediate Storage Flow Shop Scheduling under Uncertainty

Flow shop scheduling plays a very important role in process chemindustry. The method of grey chance constrained programming was researched in order to deal with the uncertainties in the complex systems in this paper. The concept of the grey uncertain programming was put forward through working over the existing uncertain programming theory. This method was used to solve the problem of having waiting-time flow shop scheduling. The concept and method of grey simulation was advanced in this paper through theoretically inducing and calculation verifying, which provide a solution method for the grey chance constrained programming. Based on the grey simulation, genetic algorithm can be used to get the best result. The effectiveness of the model and method is verified by simulation results