Discipline name
H-index
Citations
Publications
World Ranking
National Ranking

Computer Science
H-index
56
Citations
10,384
196
World Ranking
2067
National Ranking
1145

- Algorithm
- Combinatorics
- Computer network

His primary areas of study are Combinatorics, Approximation algorithm, Discrete mathematics, Steiner tree problem and Mathematical optimization. His study on Combinatorics is mostly dedicated to connecting different topics, such as k-minimum spanning tree. The Approximation algorithm study combines topics in areas such as Network planning and design, Graph, Computational complexity theory, Time complexity and Node.

His research integrates issues of Travelling salesman problem and Metric in his study of Discrete mathematics. His Mathematical optimization study combines topics from a wide range of disciplines, such as Algorithm and Small set. His Spanning tree research includes elements of Triangle inequality and Minimum spanning tree.

- When Trees Collide: An Approximation Algorithm for theGeneralized Steiner Problem on Networks (355 citations)
- A Nearly best-possible approximation algorithm for node-weighted Steiner trees (318 citations)
- A Polylogarithmic Approximation Algorithm for the Group Steiner Tree Problem (234 citations)

His scientific interests lie mostly in Approximation algorithm, Combinatorics, Mathematical optimization, Discrete mathematics and Steiner tree problem. His research investigates the link between Approximation algorithm and topics such as Stochastic optimization that cross with problems in Stochastic programming and Vertex cover. His study explores the link between Combinatorics and topics such as Linear programming relaxation that cross with problems in Rounding.

The Discrete mathematics study combines topics in areas such as Online algorithm and Metric. His studies in Steiner tree problem integrate themes in fields like Tree and Algorithm. The concepts of his Spanning tree study are interwoven with issues in Minimum spanning tree and Gomory–Hu tree.

- Approximation algorithm (46.11%)
- Combinatorics (40.35%)
- Mathematical optimization (28.24%)

- Approximation algorithm (46.11%)
- Mathematical optimization (28.24%)
- Combinatorics (40.35%)

R. Ravi mainly investigates Approximation algorithm, Mathematical optimization, Combinatorics, Discrete mathematics and Computer network. His Approximation algorithm research is multidisciplinary, relying on both Node, Travelling salesman problem, Bipartite graph and Metric space. His work carried out in the field of Mathematical optimization brings together such families of science as Routing, Sequence and Vertex.

His Combinatorics research is multidisciplinary, incorporating elements of Upper and lower bounds, Rounding and Linear programming relaxation. A large part of his Discrete mathematics studies is devoted to Steiner tree problem. The various areas that he examines in his Steiner tree problem study include Covering problems and Online algorithm.

- Post Processing Recommender Systems for Diversity (27 citations)
- Robust and MaxMin Optimization under Matroid and Knapsack Uncertainty Sets (24 citations)
- The Performances Analysis of Fast Efficient Lossless Satellite Image Compression and Decompression for Wavelet Based Algorithm (20 citations)

- Algorithm
- Computer network
- Statistics

The scientist’s investigation covers issues in Approximation algorithm, Mathematical optimization, Combinatorics, Travelling salesman problem and Artificial intelligence. His Approximation algorithm research includes themes of Graph, Theoretical computer science, Knapsack problem, Combinatorial optimization and Bipartite graph. His Knapsack problem study incorporates themes from Submodular set function, Online algorithm, Matroid and Steiner tree problem.

The study incorporates disciplines such as Metric and Metric space in addition to Mathematical optimization. His research in Combinatorics intersects with topics in Discrete mathematics, Convex combination and Linear programming relaxation. His Travelling salesman problem study also includes fields such as

- Vertex together with Shortest-path tree, Minimum spanning tree, Decision tree and Optimal decision,
- Special case which connect with Minimum weight and Polyhedral analysis.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

When Trees Collide: An Approximation Algorithm for theGeneralized Steiner Problem on Networks

Ajit Agrawal;Philip Klein;R. Ravi.

SIAM Journal on Computing **(1995)**

597 Citations

A Nearly best-possible approximation algorithm for node-weighted Steiner trees

Philip N. Klein;R. Ravi.

Journal of Algorithms **(1992)**

428 Citations

A Polylogarithmic Approximation Algorithm for the Group Steiner Tree Problem

Naveen Garg;Goran Konjevod;R. Ravi.

Journal of Algorithms **(2000)**

384 Citations

Spanning Trees---Short or Small

R. Ravi;R. Sundaram;M. V. Marathe;D. J. Rosenkrantz.

SIAM Journal on Discrete Mathematics **(1996)**

255 Citations

Rapid rumor ramification: approximating the minimum broadcast time

R. Ravi.

foundations of computer science **(1994)**

252 Citations

Bicriteria Network Design Problems

Madhav V Marathe;R Ravi;Ravi Sundaram;S.S Ravi.

Journal of Algorithms **(1998)**

218 Citations

Hedging Uncertainty: Approximation Algorithms for Stochastic Optimization Problems

R. Ravi;Amitabh Sinha.

Mathematical Programming **(2006)**

207 Citations

A Polynomial-Time Approximation Scheme for Minimum Routing Cost Spanning Trees

Bang Ye Wu;Giuseppe Lancia;Vineet Bafna;Kun-Mao Chao.

SIAM Journal on Computing **(1999)**

203 Citations

Boosted sampling: approximation algorithms for stochastic optimization

Anupam Gupta;Martin Pál;R. Ravi;Amitabh Sinha.

symposium on the theory of computing **(2004)**

195 Citations

Many birds with one stone: multi-objective approximation algorithms

R. Ravi;M. V. Marathe;S. S. Ravi;D. J. Rosenkrantz.

symposium on the theory of computing **(1993)**

193 Citations

Profile was last updated on December 6th, 2021.

Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).

The ranking h-index is inferred from publications deemed to belong to the considered discipline.

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