Broken-Edge Decision-Making Strategy for COVID-19 over Air Railway Composite Network

Table 3

Strategy algorithm.

Step 1	Randomly generate cities in different states, set the maximum time limit for controlling epidemics, tmax, and set the number of iterations, n.
Step 2	Filter out nodes located in states T1 and T2 and find out all possible broken edges. Randomly generate recovered periods τi.
Step 3	Randomly cut off partially broken edges and record them.
Step 4	Calculate the current economic losses.
Step 5	Determine each node state for the next time according to the ARCN-SUTS model. Cities located in state T1 or state T2 will return to state S at the next moment. If the state for the broken-edge city is not state T1 or state T2, reconnect the broken edge; otherwise, keep broken.
Step 6	If the number of nodes in state S is equal to the total number of nodes, go to step 7. If the number of nodes in state S is not equal to the total number of nodes, and the date has not reached the maximum time limit tmax for controlling the epidemics, go to step 2. If the date reaches the maximum time limit tmax to control the epidemic, go to step 8.
Step 7	Record the total economic losses and date.
Step 8	Keep the initial city state; if the set iteration number, n, is not reached, go to step 2; otherwise, end.