I have an industrial problem which I'm trying to cast as a Traveling Salesman problem (TSP) in 3D euclidian space. There are physical limitations which implies that some subpaths may or may not be valid based on simple rules.What algorithm is best to deal with the TSP given that there are rules/model/constraints?It could be done with Genetic algorithms for example, but the only way i see how to incorporate those rules is by including them somehow within the fitness function. But i feel there should be more suitable approaches.Would reinforcement Q-learning or other algorithms be more appropriate for a rule-based euclidian TSP?
Traveling Salesman variant: best approach?
machine learning;graphs;reinforcement learning;genetic algorithms