Applications, challenges, and solutions to single- and multi-objective critical node detection problems: a survey

Recognizing critical nodes in complex networks has emerged as a challenging task across several application areas. The critical node detection problem (CNDP) is an optimization challenge that entails determining the subset of nodes whose removal adversely affects network connectivity and performance based on certain predetermined criteria. The problem of recognizing critical nodes has received significant consideration since it is a vital challenge in a multitude of application areas. As a result, many variants have been proposed on the basis of numerous metrics. In this survey, we discuss different applications, challenges, and solutions to single- and multi-objective CNDP. We review and classify different recent advancements and obtained outcomes for each variant, proposed from 2017 to 2022. To our best knowledge, this is the first survey on the heuristic optimization-based solutions for CNDP that have been developed in recent years. This study also provides researchers with future insight into filling gaps in the critical nodes research field and identifying emerging research trends in this area.