Ant Colony Optimization - Part 5: Example - Traveling Saleman Problem (TSP)

[@gustavorolim5706]

Great video. It helped a lot to implement the algorithm in the context of machine scheduling.

[@m0elj0n0]

Prof Lam, At 11:50 for the AS method: why the contributions from ant 1, 2 and 5 are 1/15? Would you please elaborate on this? Should they be the same as SACO (1/35, 1/55, 1/40)? Thank you.

[@hklam2368]

Thanks for your comment. The contributions from 1, 2 and 5 are 1/15 because they follow the Ant-quantity AS contribution rule given on the bottom right-hand side of the slide at 11:50. The update rule is Q/d_{ij}(t).

[@dylanmortimer5815]

Super helpful video, thanks heaps : )

[@HM-wm7xk]

Hi, I can see this Salesmen Travelling Problem is symmetric, i.e., the distance matrix is symmetrical, the distance traveled between two points is the same. By the same way, can I proposed the pheromone travelled between two points in this problem be the same? i.e, the pheromone matrix is symmetrical in the Salesmen Travelling Problem? Will this through affect the solution?

[@shivambhushan5080]

Sir please explain, if the original path chosen for each ant in the beginning is through transition probabilities and if yes how, or if it is random

[@anonymousvevo8697]

Thank you professor

[@hklam2368]

Thank you.

[@anonymousvevo8697]

@@hklam2368 Can i contact you regarding this presentation there is point i didn't understand and I'm working on a AI project? thanks

[@hildur7168]

Very helpful!

[@Darklaki1]

thank you sir

[@PivotStickmanAnimations]

always nice to learn a thing or two from elon musk.

[@securityK]

支持