4 ms·
From what I read there I think he assumes he is always visiting his homebase in between. But when he travels in one day from client A directly to client B (and
by therealmarv 10y ago
From what I read there I think he assumes he is always visiting his homebase in between. But when he travels in one day from client A directly to client B (and even C) without visiting his homebase the stuff get's much more complex and results may vary. If you want to know more do research about the "traveling salesman problem". TL;DR: It's not so easy.
- onion2k 10y agoIf you want to know more do research about the "traveling salesman problem". TL;DR: It's not so easy. It's not easy to optimize the travelling salesman problem, but if you're happy to brute force it using 30B searches it's incredibly straightforward.
- foota 10y agoFor a small number of clients tsp isn't so bad. The best known exact algorithm is n^2*2^n. And absolutely trivial for the approximate solution algorithms.
- andreareina 10y agoCould be that he only works by the day, so going from client A to client B will be rare. Disregarding changes in travel time due to the different time of say, we know that A -> Origin + Origin -> B is an upper bound on A -> B so the solution is still good even if it's not quite optimal.
- therealmarv 10y agoYes you're right. It all depends on amount of clients he visits in one day, if they are flexible in time or not and how to get from client A to client B (or C).
- deleted 10y ago[deleted]
- kayoone 10y agousually development contract jobs are for weeks/months so i think usually you would go only to one client per day.
- adrianN 10y agoTSP is actually pretty easy as NP-hard problems go, because it's important in practice (chip layout!) and hence gets considerable attention. Instances with millions of cities can be solved nearly to optimality.