Robust Flexible Job Shop Scheduling Problem Research Based On Invulnerability Measure Value Of Complex Network

The efficiency and stability of scheduling scheme should be taken into consideration simultaneously.On the present research,accurate proper models were set,many algorithms were created.Flexible job shop scheduling problem contains complex network relationship as there are complicated relationship between part?operations and machines.New instructed flash for scheduling could be gotten by analysing the relationships between nodes and edges,which cannot be obtained by current math models.Assuming that the invulnerability of complex network is related to the robustness of scheduling scheme,as the topology behaviors show dynamic events for scheduling plan when we set complex network.The robustness of scheduling scheme could be improved based on invulnerability measure of complex network.In this paper,robust flexible job shop scheduling based on invulnerability measure of complex network is studied.(1)Setting a directed weighted complex network model while machines as nodes.Analysing the network topological characteristics related to scheduling,node degree and edge weight,the invulnerability measure.(2)The network topology behaviors show dynamic events for scheduling plan,It is concluded that the scheduling scheme with large invulnerability measure value of complex network has better robustness.(3)Confirmed the relationship between the invulnerability measure and the robustness of scheduling scheme.The invulnerability measure decreases as deleting nodes and edges,meanwhile the robustness of the corresponding scheduling scheme becomes worse.(4)The robustness of scheduling scheme could be improved based on invulnerability measure of complex network.Taking the invulnerability measure as the characteristics of the robustness of scheduling scheme,and considering the minimum makespan.In the contrast experiment,considering the minimum makespan.The experiment verifies that the invulnerability measure has better robustness,by companying the robustness index RM2.