Researchers, students, and engineers in computer science, big data, applied mathematics, operations research, algorithm design, artificial intelligence, software engineering, data analysis, industrial and systems engineering will benefit from the state-of-the-art results presented in modern graph theory and its applications to the design of efficient algorithms for optimization problems. 

Topics covered in this work include:

·         Graphs where maximal cliques and stable sets intersect

·         The maximum independent set problem with special classes

·         A general technique for heuristic algorithms for optimization problems

·         The network design problem with cut constraints

·         Algorithms for computing the frustration index of a signed graph

·         A heuristic approach for studying the patrol problem on a graph

·         Structural and algorithmic results on branchings in digraphs

·         Improved upper bounds for Korkel--Ghosh benchmark SPLP instances