  We present a polynomial-time approximation scheme (PTAS) for the min-max
multiple TSP problem in Euclidean space, where multiple traveling salesmen are
tasked with visiting a set of $n$ points and the objective is to minimize the
maximum tour length. For an arbitrary $\varepsilon > 0$, our PTAS achieves a
$(1 + \varepsilon)$-approximation in time $O \big(n ((1/\varepsilon) \log
(n/\varepsilon))^{O(1/\varepsilon)} \big)$. Our approach extends Sanjeev
Arora's dynamic-programming (DP) PTAS for the Euclidean TSP
(https://doi.org/10.1145/290179.290180). Our algorithm introduces a rounding
process to balance the allocation of path lengths among the multiple salesman.
We analyze the accumulation of error in the DP to prove that the solution is a
$(1 + \varepsilon)$-approximation.
