The smoothed number of Pareto-optimal solutions in bicriteria integer optimization

成果类型:
Article
署名作者:
Beier, Rene; Roeglin, Heiko; Roesner, Clemens; Voecking, Berthold
署名单位:
Max Planck Society; University of Bonn; RWTH Aachen University
刊物名称:
MATHEMATICAL PROGRAMMING
ISSN/ISSBN:
0025-5610
DOI:
10.1007/s10107-022-01885-6
发表日期:
2023
页码:
319-355
关键词:
shortest paths algorithms Knapsack
摘要:
A well-established heuristic approach for solving bicriteria optimization problems is to enumerate the set of Pareto-optimal solutions. The heuristics following this principle are often successful in practice. Their running time, however, depends on the number of enumerated solutions, which is exponential in the worst case. We study bicriteria integer optimization problems in the model of smoothed analysis, in which inputs are subject to a small amount of random noise, and we prove an almost tight polynomial bound on the expected number of Pareto-optimal solutions. Our results give rise to tight polynomial bounds for the expected running time of the Nemhauser-Ullmann algorithm for the knapsack problem and they improve known results on the running times of heuristics for the bounded knapsack problem and the bicriteria shortest path problem.
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