论文信息 - When are NP-hard location problems easy?

When are NP-hard location problems easy?

We discuss in this paper several location problems for which it is an NP-hard problem to find an approximate solution. Given certain assumptions on the input distributions, we present polynomial algorithms that deliver a solution asymptotically close to the optimum with probability that is asymptotically one (the exact nature of this asymptotic convergence is described in the paper). In that sense the subproblems defined on the specified family of inputs are in fact easy.

Dorit S. Hochbaum | D. Hochbaum

[1] Maurizio Talamo,et al. Probabilistic Analysis of Two Euclidean Location Problems , 1983, RAIRO Theor. Informatics Appl..

[2] Dorit S. Hochbaum,et al. Heuristics for the fixed cost median problem , 1982, Math. Program..

[3] Richard M. Karp,et al. Probabilistic Analysis of Partitioning Algorithms for the Traveling-Salesman Problem in the Plane , 1977, Math. Oper. Res..

[4] Christos H. Papadimitriou,et al. Worst-Case and Probabilistic Analysis of a Geometric Location Problem , 1981, SIAM J. Comput..

[5] D. Hochbaum. Easy Solutions for the K–Center Problem or the Dominating Set Problem on Random Graphs , 1985 .

[6] Victor Klee,et al. Combinatorial Optimization: What is the State of the Art , 1980, Math. Oper. Res..

[7] J. Steele,et al. Steinhaus's geometric location problem for random samples in the plane , 1982, Advances in Applied Probability.

[8] Eitan Zemel. Probabilistic Analysis of Geometric Location Problems , 1985 .

[9] M. L. Fisher,et al. Probabilistic Analysis of the Planar k-Median Problem , 1980, Math. Oper. Res..

[10] Alan M. Frieze,et al. Probabilistic analysis of some euclidean clustering problems , 1980, Discret. Appl. Math..