自然W[P]-完全极小化问题的逼近性

Kord Eickmeyer, Martin Grohe, M. Grüber
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引用次数: 22

摘要

证明了加权单调电路可满足性问题不存在具有常数或多对数近似比的定参数可处理逼近算法,除非FPT = W[P]。我们的结果回答了Alekhnovich和Razborov的一个问题,他们证明了加权单调电路可满足性问题没有固定参数可处理的2逼近算法,除非W[P]中的每个问题都可以用随机化的fpt算法求解,并询问了他们的结果是否可以非随机化。Alekhnovich和Razborov用他们的不可逼近性结果作为引理来证明除非W[P]包含在随机FPT中,否则分辨率是不可自动化的。我们的结果的直接结果是,复杂性理论假设可以被削弱为W[P] ne FPT。已知单调电路可满足性问题的决策版本对于W[P]类是完全的。通过适当的近似保留约简,我们证明了所有其他已知W[P]-完全的自然最小化问题的类似的不可逼近性结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Approximation of Natural W[P]-Complete Minimisation Problems Is Hard
We prove that the weighted monotone circuit satisfiability problem has no fixed-parameter tractable approximation algorithm with constant or polylogarithmic approximation ratio unless FPT = W[P]. Our result answers a question of Alekhnovich and Razborov, who proved that the weighted monotone circuit satisfiability problem has no fixed-parameter tractable 2-approximation algorithm unless every problem in W[P] can be solved by a randomized fpt algorithm and asked whether their result can be derandomized. Alekhnovich and Razborov used their inapproximability result as a lemma for proving that resolution is not automatizable unless W[P] is contained in randomized FPT. It is an immediate consequence of our result that the complexity theoretic assumption can be weakened to W[P] ne FPT. The decision version of the monotone circuit satisfiability problem is known to be complete for the class W[P]. By reducing them to the monotone circuit satisfiability problem with suitable approximation preserving reductions, we prove similar inapproximability results for all other natural minimisation problems known to be W[P]-complete.
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