About

The study of algorithms is at the very heart of computer science. In the last five decades, a number of significant advances have been made in the field of algorithms ranging from the development of faster algorithms to the startling discovery of some natural problems for which all known algorithms are found to be inefficient. These results triggered considerable interest in the study of algorithms, and the area of algorithm design and analysis has evolved into a field of interest. Teaching and research in this foundational aspect of computing is therefore a natural and desirable thrust area. Hence, algorithmic studies form a major component of computer science programs in colleges and universities. In the last four decades, graph and geometric problems have been studied by computer science researchers using the framework of analysis of algorithms. Graph theory is the study of the properties of graphs. Graph algorithms are one of the oldest classes of algorithms and they have been studied for almost 300 years. Graphs provide essential models for many applications areas of computer science, and at the same time, they are fascinating objects of study in pure and applied mathematics. There have been a number of exciting recent developments in graph theory that are important for designers of algorithms to know about. Correspondingly, the algorithmic viewpoint of computer science has stimulated much research in graph theory. Graph theory and graph algorithms are inseparably intertwined subjects. On the other hand, the main impetus for the development of geometric algorithms came from the progress in computer graphics, computer-aided design and manufacturing. In addi- tion, algorithms are also designed for geometric problems that are classical in nature. The success of the field can be explained from the beauty of the geometry problems studied, the solutions obtained, and by the many application domains- computer graphics, geographic information systems, robotics and others, in which geometric algorithms play a crucial role.