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This paper is motivated by real-life applications of bi-objectiveoptimization. Having many non dominated solutions, one wishes to cluster thePareto front using Euclidian distances. The p-center problems, both in thediscrete and continuous versions, are proven solvable in polynomial time with acommon dynamic programming algorithm. Having $N$ points to partition in$K\geqslant 3$ clusters, the complexity is proven in $O(KN\log N)$ (resp$O(KN\log^2 N)$) time and $O(KN)$ memory space for the continuous (respdiscrete) $K$-center problem. $2$-center problems have complexities in $O(N\logN)$. To speed-up the algorithm, parallelization issues are discussed. Aposteriori, these results allow an application inside multi-objectiveheuristics to archive partial Pareto Fronts.

Planar p-center problems are solvable in polynomial time when clustering a Pareto Front