Research On Dynamic Flexible Job Shop Scheduling Problem

Along with the shorter product life cycle and the more customers ’ individual needs, multi-product and small-batch production has become the leading production model. So the dynamic flexible job shop scheduling problem is a research hot spot now. An invasive weed optimization algorithm with discrete multi-population(IWODMP) based on the basic invasive weed optimization(IWO) is proposed, which is used to solve the flexible job shop scheduling problem(FJSP). Using IWODMP as rescheduling operator, a dynamic rescheduling algorithm solving the dynamic flexible job shop scheduling problem is proposed.In this thesis, the main research contents include:(1) According to the characteristics of scheduling problem, self-adaptive mutation and conditional exchange are used in IWO and the IWODMP is presented.(2) Studying the decoding algorithm, a matrix-decoding method is presented when the weed is decoded to an actual scheduling scheme.(3) A mathematic model of multi-objective dynamic flexible job shop scheduling problem is proposed.(4) Using rescheduling to solve the dynamic flexible job shop scheduling problem, a dynamic scheduling algorithm is proposed and it is programmed with matlab language.(5) Several examples are used to demonstrate the algorithm.The findings show that the stability of the IWODMP using to solve FJSP is better than that of other algorithm and the dynamic FJSP is solved effectively with the dynamic scheduling algorithm.