Madhav V. Marathe

TL;DR: Exploits the close relationship between circular arcs graphs and interval graphs to design efficient approximation algorithms for NP-hard optimization problems on circular arc graphs to present a heuristic for the domatic partition problem with a performance ratio of 4.

TL;DR: An experimental analysis to identify the most computational time consuming fragments of software and hardware that will likely be an integral part of power exchanges in a deregulated environment provides insights into the scalability of the system as a function of branch congestion, excess/scarcity of power, average size of multi-lateral contracts, and topology and size of networks.

TL;DR: The main contribution is the development of a unified predictive theory for characterizing the the complexity of these problems, based on the following basic two basic concepts: strongly-local replacements/reductions and relational/algebraic representability.

TL;DR: This paper presents an OpenMP-based shared-memory parallel algorithm for generating a random graph with a prescribed degree sequence, which achieves a speedup of 20.4 with 32 cores and presents a comparative study of several structural properties of the random graphs generated by the algorithm with that of the real-world graphs and random graph generated by other popular methods.

TL;DR: This work states that language recognition models of computation and associated resource bounded reductions have played a central role in characterizing the computational complexity of combinatorial problems but they typically ignore the underlying structure and semantics of the problem instances.