The-separator problem (-SP) consists of finding the minimum set of vertices whose removal
separates the network into multiple different connected components with fewer than a limited …

Finding new drugs is getting harder and harder. One of the hopes of drug discovery is to use
machine learning models to predict molecular properties. That is why models for molecular …

Recently, using a particle swarm optimizer (PSO) to guide robots in a source location
problem has attracted widespread interest. While being navigated by PSO, robots are easily …

In an intelligent transportation system, accurate traffic flow prediction can provide significant
help for travel planning. Even though some methods are proposed to do so, they focus on …

In today's semiconductor manufacturing industry, wafer foundries often face the challenge of
producing a variety of integrated circuit chip products using a single manufacturing line. To …

Detecting critical nodes in sparse graphs is important in a variety of application domains,
such as network vulnerability assessment, epidemic control, and drug design. The critical …

Shortest path problems are encountered in many engineering applications, eg, intelligent
transportation, robot path planning, and smart logistics. The environmental changes as …

Network disruption is pivotal in understanding the robustness and vulnerability of complex
networks, which is instrumental in devising strategies for infrastructure protection, epidemic …

By using an autoencoder as a dimension reduction tool, an Autoencoder-embedded
Teaching-Learning Based Optimization (ATLBO) has been proved to be effective in solving …