1. The maximum quasi-clique problem (MQCP) is an important topic in graph theory, used in many real-world applications such as complex network analysis, clustering, and bioinformatics.
2. A series of algorithms have been proposed to solve the MQCP, including exact algorithms and heuristics methods.
3. This article proposes a local search algorithm with hybrid strategies for the maximum weighted quasi-clique problem, which combines two vertex selection strategies for adding or removing vertices and introduces a probability of choosing two sub-strategies.
The article is generally reliable and trustworthy. It provides a comprehensive overview of existing algorithms for solving the MQCP, as well as an introduction to the proposed algorithm with hybrid strategies for the maximum weighted quasi-clique problem. The authors provide evidence to support their claims by citing relevant research papers and experiments conducted on various graphs including synthetic graphs and real-world networks.
The article does not appear to be biased or one-sided in its reporting; it presents both sides equally by providing an overview of existing algorithms as well as introducing the proposed algorithm with hybrid strategies. Furthermore, it does not contain any promotional content or partiality towards any particular method or approach.
The article does not appear to be missing any points of consideration or evidence for its claims; all relevant information is provided in detail throughout the text. Additionally, possible risks are noted when discussing the application of graph theory in real-world scenarios such as complex network analysis, clustering, and bioinformatics.
In conclusion, this article is reliable and trustworthy due to its comprehensive coverage of existing algorithms for solving the MQCP as well as its introduction to the proposed algorithm with hybrid strategies for the maximum weighted quasi-clique problem.