This occurs in B at index 4. Inversion Mutation is often used in GAs as a way of adding random variation to the evolving population, preventing a total loss of diversity. In our case it's not so useful, however, as a mutation has a high probability of resulting in a non-viable city order. We may still wish to apply a small mutation rate, provided of course we account for non-viable city orders in the evaluation function. However, an alternative to mutation is perhaps more appropriate.
Inversion refers to the randomised exchange of alleles in chromosomes.
Hence, allele positions 2 and 7 have been exchanged. I've previously tried this approach to the Travelling Salesman Problem and ran it successfully with city counts of between 100 and 1000. Figure 1a shows an initial randomly ordered route between 100 randomly positioned points. Figure 1b, after around 10,000 generations.