1 research outputs found
Balanced dynamic multiple travelling salesmen: algorithms and continuous approximations
Dynamic routing occurs when customers are not known in advance, e.g. for
real-time routing. Two heuristics are proposed that solve the balanced dynamic
multiple travelling salesmen problem (BD-mTSP). These heuristics represent
operational (tactical) tools for dynamic (online, real-time) routing. Several
types and scopes of dynamics are proposed. Particular attention is given to
sequential dynamics. The balanced dynamic closest vehicle heuristic (BD-CVH)
and the balanced dynamic assignment vehicle heuristic (BD-AVH) are applied to
this type of dynamics. The algorithms are tested for instances in the Euclidean
plane. Continuous approximation models for the BD-mTSP's are derived and serve
as strategic tools for dynamic routing. The models express route lengths using
vehicles, customers and dynamic scopes without the need of running an
algorithm. A machine learning approach was used to obtain regression models.
The mean-average-percentage error of two of these models is below 3%.Comment: 15 pages, 10 figures, 7 tables, 2 heuristics, 3 CAM model