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- Gerhard J. Woeginger

Computer Science

Germany

2023

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

Mathematics
D-index
67
Citations
14,211
451
World Ranking
244
National Ranking
11

Computer Science
D-index
67
Citations
14,014
454
World Ranking
1407
National Ranking
47

2023 - Research.com Computer Science in Germany Leader Award

2014 - Member of Academia Europaea

- Algorithm
- Combinatorics
- Statistics

Combinatorics, Scheduling, Mathematical optimization, Approximation algorithm and Discrete mathematics are his primary areas of study. His biological study spans a wide range of topics, including Algorithm, Combinatorial optimization and Worst case ratio. His studies deal with areas such as Upper and lower bounds, Competitive analysis, Online algorithm and Randomized algorithm as well as Scheduling.

His work carried out in the field of Mathematical optimization brings together such families of science as Dynamic priority scheduling, Open-shop scheduling, Round-robin scheduling and Fair-share scheduling. His Approximation algorithm study combines topics in areas such as Assignment problem and Bounded function. His Discrete mathematics research is multidisciplinary, relying on both Tournament and Transitive relation.

- Exact algorithms for NP-hard problems: a survey (490 citations)
- Online algorithms : The state of the art (318 citations)
- A Review of Machine Scheduling: Complexity, Algorithms and Approximability (244 citations)

Gerhard J. Woeginger mainly investigates Combinatorics, Discrete mathematics, Time complexity, Mathematical optimization and Computational complexity theory. His research integrates issues of Travelling salesman problem and Combinatorial optimization in his study of Combinatorics. Many of his studies on Discrete mathematics apply to Quadratic assignment problem as well.

His studies in Time complexity integrate themes in fields like Distance matrix, Bounded function, Set and Special case. His Mathematical optimization research incorporates elements of Scheduling, Flow shop scheduling and Job shop scheduling. His Computational complexity theory research is multidisciplinary, relying on both Assignment problem, Optimization problem and Theoretical computer science.

- Combinatorics (52.19%)
- Discrete mathematics (27.67%)
- Time complexity (26.62%)

- Combinatorics (52.19%)
- Computational complexity theory (21.37%)
- Discrete mathematics (27.67%)

The scientist’s investigation covers issues in Combinatorics, Computational complexity theory, Discrete mathematics, Time complexity and Mathematical optimization. His work in Combinatorics tackles topics such as Matrix which are related to areas like Dynamic programming. His Computational complexity theory study integrates concerns from other disciplines, such as Robust optimization, Assignment problem, Mathematical economics, Set and Optimization problem.

The Discrete mathematics study combines topics in areas such as Quadratic assignment problem, Preference, Special case and Travelling salesman problem. His studies deal with areas such as Monotone polygon, Quadratic equation, Matching, Knapsack problem and Decision problem as well as Time complexity. His study in Mathematical optimization is interdisciplinary in nature, drawing from both Element, Job shop scheduling and Fair-share scheduling.

- A characterization of the single-crossing domain (56 citations)
- The (Weighted) Metric Dimension of Graphs: Hard and Easy Cases (42 citations)
- Parameterized algorithmics for computational social choice: Nine research challenges (42 citations)

- Algorithm
- Combinatorics
- Statistics

His primary areas of study are Combinatorics, Computational complexity theory, Discrete mathematics, Time complexity and Parameterized complexity. His Combinatorics study frequently draws connections to adjacent fields such as Point. His work deals with themes such as Mathematical economics, Combinatorial optimization and Computational problem, which intersect with Computational complexity theory.

He has included themes like Assignment problem, Quadratic assignment problem, Preference and Special case in his Discrete mathematics study. As a member of one scientific family, Gerhard J. Woeginger mostly works in the field of Parameterized complexity, focusing on Scheduling and, on occasion, Distributed computing. His biological study spans a wide range of topics, including Simple and Job shop scheduling.

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.

Exact algorithms for NP-hard problems: a survey

Gerhard J. Woeginger.

Combinatorial optimization - Eureka, you shrink! **(2003)**

908 Citations

Online algorithms : The state of the art

Amos Fiat;Gerhard J. Woeginger.

Lecture Notes in Computer Science **(1998)**

488 Citations

A Review of Machine Scheduling: Complexity, Algorithms and Approximability

Bo Chen;Chris N. Potts;Gerhard J. Woeginger.

Handbook of combinatorial optimization, volume 3 **(1998)**

457 Citations

Approximability and Nonapproximability Results for Minimizing Total Flow Time on a Single Machine

Hans Kellerer;T. Tautenhahn;G. Woeginger.

SIAM Journal on Computing **(1999)**

301 Citations

When Does a Dynamic Programming Formulation Guarantee the Existence of a Fully Polynomial Time Approximation Scheme (FPTAS)

Gerhard J. Woeginger.

Informs Journal on Computing **(2000)**

267 Citations

Non-Approximability Results for Scheduling Problems with Minsum Criteria

Han Hoogeveen;Petra Schuurman;Gerhard J. Woeginger.

Informs Journal on Computing **(2001)**

253 Citations

On-line Packing and Covering Problems

János Csirik;Gerhard J. Woeginger.

Lecture Notes in Computer Science **(1998)**

240 Citations

Approximation schemes for scheduling on parallel machines

Noga Alon;Yossi Azar;Gerhard J. Woeginger;Tal Yadid.

Journal of Scheduling **(1998)**

233 Citations

A polynomial-time approximation scheme for maximizing the minimum machine completion time

Gerhard J. Woeginger.

Operations Research Letters **(1997)**

206 Citations

Uncapacitated single and multiple allocation p-hub center problems

Andreas T. Ernst;Horst Hamacher;Houyuan Jiang;Mohan Krishnamoorthy.

Computers & Operations Research **(2009)**

205 Citations

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