Gábor Galambos

809 total citations
14 papers, 211 citations indexed

About

Gábor Galambos is a scholar working on Industrial and Manufacturing Engineering, Computer Networks and Communications and Electrical and Electronic Engineering. According to data from OpenAlex, Gábor Galambos has authored 14 papers receiving a total of 211 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Industrial and Manufacturing Engineering, 11 papers in Computer Networks and Communications and 4 papers in Electrical and Electronic Engineering. Recurrent topics in Gábor Galambos's work include Optimization and Search Problems (10 papers), Optimization and Packing Problems (9 papers) and Scheduling and Optimization Algorithms (6 papers). Gábor Galambos is often cited by papers focused on Optimization and Search Problems (10 papers), Optimization and Packing Problems (9 papers) and Scheduling and Optimization Algorithms (6 papers). Gábor Galambos collaborates with scholars based in Hungary, Austria and Germany. Gábor Galambos's co-authors include Gerhard J. Woeginger, József Békési, János Balogh, Hans Kellerer, Gerhard Reinelt, Marcus Oswald, György Dósa, Zhiyi Tan, André van Vliet and Ulrich Pferschy and has published in prestigious journals such as European Journal of Operational Research, SIAM Journal on Computing and Theoretical Computer Science.

In The Last Decade

Gábor Galambos

13 papers receiving 198 citations

Peers

Gábor Galambos
Gábor Galambos
Citations per year, relative to Gábor Galambos Gábor Galambos (= 1×) peers Héctor Joaquín Fraire Huacuja

Countries citing papers authored by Gábor Galambos

Since Specialization
Citations

This map shows the geographic impact of Gábor Galambos's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Gábor Galambos with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gábor Galambos more than expected).

Fields of papers citing papers by Gábor Galambos

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Gábor Galambos. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Gábor Galambos. The network helps show where Gábor Galambos may publish in the future.

Co-authorship network of co-authors of Gábor Galambos

This figure shows the co-authorship network connecting the top 25 collaborators of Gábor Galambos. A scholar is included among the top collaborators of Gábor Galambos based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Gábor Galambos. Gábor Galambos is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

14 of 14 papers shown
1.
Békési, József, György Dósa, & Gábor Galambos. (2021). A first Fit type algorithm for the coupled task scheduling problem with unit execution time and two exact delays. European Journal of Operational Research. 297(3). 844–852. 3 indexed citations
2.
Balogh, János, József Békési, Gábor Galambos, György Dósa, & Zhiyi Tan. (2016). Lower bound for 3-batched bin packing. Discrete Optimization. 21. 14–24. 8 indexed citations
3.
Békési, József, et al.. (2014). A branch-and-bound algorithm for the coupled task problem. Mathematical Methods of Operations Research. 80(1). 47–81. 4 indexed citations
4.
Balogh, János, József Békési, & Gábor Galambos. (2012). New lower bounds for certain classes of bin packing algorithms. Theoretical Computer Science. 440-441. 1–13. 55 indexed citations
5.
Balogh, János, József Békési, Gábor Galambos, & Gerhard Reinelt. (2012). On-line bin packing with restricted repacking. Journal of Combinatorial Optimization. 27(1). 115–131. 7 indexed citations
6.
Balogh, János, József Békési, Gábor Galambos, & Mihály Csaba Markót. (2009). Improved lower bounds for semi-online bin packing problems. Computing. 84(1-2). 139–148. 2 indexed citations
7.
Békési, József, Gábor Galambos, Marcus Oswald, & Gerhard Reinelt. (2008). Improved analysis of an algorithm for the coupled task problem with UET jobs. Operations Research Letters. 37(2). 93–96. 8 indexed citations
8.
Balogh, János, József Békési, Gábor Galambos, & Gerhard Reinelt. (2008). Lower Bound for the Online Bin Packing Problem with Restricted Repacking. SIAM Journal on Computing. 38(1). 398–410. 9 indexed citations
9.
Békési, József, Gábor Galambos, & Hans Kellerer. (2000). A 5/4 Linear Time Bin Packing Algorithm. Journal of Computer and System Sciences. 60(1). 145–160. 28 indexed citations
10.
Békési, József, Gábor Galambos, & Peter I. Hajnal. (2000). Analysis of permutation routing algorithms. European Journal of Operational Research. 125(2). 249–256.
11.
Békési, József, Gábor Galambos, Ulrich Pferschy, & Gerhard J. Woeginger. (1997). Greedy Algorithms for On-Line Data Compression. Journal of Algorithms. 25(2). 274–289. 2 indexed citations
12.
Chen, Bo, et al.. (1997). A Note on "An On-Line Scheduling Heuristic with Better Worst Case Ratio than Graham's List Scheduling". SIAM Journal on Computing. 26(3). 870–872. 5 indexed citations
13.
Galambos, Gábor, Hans Kellerer, & Gerhard J. Woeginger. (1993). A Lower Bound for On-Line Vector-Packing Algorithms.. Acta Cybernetica. 11. 23–34. 14 indexed citations
14.
Galambos, Gábor & Gerhard J. Woeginger. (1993). An On-Line Scheduling Heuristic with Better Worst-Case Ratio Than Graham’s List Scheduling. SIAM Journal on Computing. 22(2). 349–355. 66 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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