参数化近似技术

IF 12.7 1区计算机科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS

Computer Science Review Pub Date : 2025-10-04 DOI:10.1016/j.cosrev.2025.100833

Ariel Kulik , Hadas Shachnai

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引用次数: 0

摘要

逼近算法和参数化复杂度是处理np困难问题的两种经典方法。结合这两种方法的参数化近似领域近年来蓬勃发展，有无数的算法结果和下界。在本调查中，我们介绍了该领域，并强调了一些主要的技术开发的设计参数化近似算法和导出硬度结果。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Techniques in parameterized approximation

Approximation algorithms and parameterized complexity are two classic approaches for coping with NP-hard problems. The field of parameterized approximation which combines the two approaches has flourished in recent years, with a myriad of algorithmic results as well as lower bounds. In this survey we give an introduction to the field and highlight some of the main techniques developed for the design of parameterized approximation algorithms and for deriving hardness results.

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来源期刊

Computer Science Review Computer Science-General Computer Science

CiteScore

32.70

自引率

0.00%

发文量

审稿时长

51 days

期刊介绍： Computer Science Review, a publication dedicated to research surveys and expository overviews of open problems in computer science, targets a broad audience within the field seeking comprehensive insights into the latest developments. The journal welcomes articles from various fields as long as their content impacts the advancement of computer science. In particular, articles that review the application of well-known Computer Science methods to other areas are in scope only if these articles advance the fundamental understanding of those methods.