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- Daniel Bienstock

Discipline name
D-index
D-index (Discipline H-index) only includes papers and citation values for an examined
discipline in contrast to General H-index which accounts for publications across all
disciplines.
Citations
Publications
World Ranking
National Ranking

Engineering and Technology
D-index
34
Citations
5,980
98
World Ranking
3852
National Ranking
1466

Mathematics
D-index
37
Citations
6,301
114
World Ranking
1671
National Ranking
733

Computer Science
D-index
38
Citations
6,549
117
World Ranking
6449
National Ranking
3096

2013 - Fellow of the Institute for Operations Research and the Management Sciences (INFORMS)

- Mathematical optimization
- Computer network
- Algorithm

The scientist’s investigation covers issues in Mathematical optimization, Integer programming, Combinatorics, Graph and Power grid. Mathematical optimization and Network control are commonly linked in his work. His research in Integer programming intersects with topics in Multi-commodity flow problem, Flow network, Computation, Scale and Upper and lower bounds.

His work in Computation tackles topics such as Network planning and design which are related to areas like Telecommunications network. His Upper and lower bounds research includes themes of Branch and cut, Quadratic programming, Criss-cross algorithm and Knapsack problem. He has researched Graph in several fields, including Characterization, Minor, Isomorphism and Treewidth.

- Computational study of a family of mixed-integer quadratic programming problems (322 citations)
- Potential Function Methods for Approximately Solving Linear Programming Problems: Theory and Practice (296 citations)
- Chance-Constrained Optimal Power Flow: Risk-Aware Network Control under Uncertainty ∗ (289 citations)

His primary scientific interests are in Mathematical optimization, Combinatorics, Discrete mathematics, Integer programming and Optimization problem. In his works, Daniel Bienstock undertakes multidisciplinary study on Mathematical optimization and Stochastic process. His Combinatorics study combines topics from a wide range of disciplines, such as Bounded function and Knapsack problem.

His work in the fields of Knapsack problem, such as Continuous knapsack problem, overlaps with other areas such as Covering problems. His Discrete mathematics research includes elements of Polynomial optimization and Relaxation. Daniel Bienstock works in the field of Integer programming, focusing on Branch and cut in particular.

- Mathematical optimization (42.75%)
- Combinatorics (28.99%)
- Discrete mathematics (23.91%)

- Mathematical optimization (42.75%)
- Discrete mathematics (23.91%)
- Linear programming (7.25%)

His main research concerns Mathematical optimization, Discrete mathematics, Linear programming, Polynomial optimization and Stochastic process. Mathematical optimization is closely attributed to Theory of computation in his study. Daniel Bienstock interconnects Graph and Linear programming relaxation in the investigation of issues within Discrete mathematics.

The concepts of his Linear programming study are interwoven with issues in Complex number, Flow and Nonlinear system. His Polynomial optimization research is multidisciplinary, incorporating elements of Treewidth, Polynomial inequalities and Dimension. His Computation study incorporates themes from Control system and Robustness.

- Strong NP-hardness of AC power flows feasibility (20 citations)
- Chance-Constrained Unit Commitment With N-1 Security and Wind Uncertainty (11 citations)
- LP Formulations for Polynomial Optimization Problems (11 citations)

- Mathematical optimization
- Computer network
- Algebra

Daniel Bienstock mainly investigates Mathematical optimization, Stochastic process, Discrete mathematics, Linear programming and Topology. His study on Mathematical optimization is mostly dedicated to connecting different topics, such as Control. Variance, Work, Control system and Computation are fields of study that intersect with his Stochastic process study.

His work in the fields of Treewidth overlaps with other areas such as Class. He has included themes like Time complexity, Deep learning, Artificial intelligence, Exponential function and Polynomial in his Linear programming study. Topology is intertwined with AC power, Flow system and Materials science in his study.

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.

Computational study of a family of mixed-integer quadratic programming problems

Daniel Bienstock.

Mathematical Programming **(1996)**

495 Citations

Computational study of a family of mixed-integer quadratic programming problems

Daniel Bienstock.

Mathematical Programming **(1996)**

495 Citations

Chance-Constrained Optimal Power Flow: Risk-Aware Network Control under Uncertainty ∗

Daniel Bienstock;Michael Chertkov;Sean Harnett.

Siam Review **(2014)**

472 Citations

Chance-Constrained Optimal Power Flow: Risk-Aware Network Control under Uncertainty ∗

Daniel Bienstock;Michael Chertkov;Sean Harnett.

Siam Review **(2014)**

472 Citations

A note on the prize collecting traveling salesman problem

Daniel Bienstock;Michel X. Goemans;David Simchi-Levi;David Williamson.

Mathematical Programming **(1993)**

328 Citations

A note on the prize collecting traveling salesman problem

Daniel Bienstock;Michel X. Goemans;David Simchi-Levi;David Williamson.

Mathematical Programming **(1993)**

328 Citations

Monotonicity in graph searching

D. Bienstock;Paul Seymour.

Journal of Algorithms **(1991)**

326 Citations

Monotonicity in graph searching

D. Bienstock;Paul Seymour.

Journal of Algorithms **(1991)**

326 Citations

Capacitated Network Design—Polyhedral Structure and Computation

Daniel Bienstock;Oktay Günlük.

Informs Journal on Computing **(1996)**

306 Citations

Capacitated Network Design—Polyhedral Structure and Computation

Daniel Bienstock;Oktay Günlük.

Informs Journal on Computing **(1996)**

306 Citations

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