Sergey Shebalov

540 total citations
11 papers, 347 citations indexed

About

Sergey Shebalov is a scholar working on Management Information Systems, Industrial and Manufacturing Engineering and Transportation. According to data from OpenAlex, Sergey Shebalov has authored 11 papers receiving a total of 347 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Management Information Systems, 5 papers in Industrial and Manufacturing Engineering and 4 papers in Transportation. Recurrent topics in Sergey Shebalov's work include Supply Chain and Inventory Management (7 papers), Transportation Planning and Optimization (4 papers) and Vehicle Routing Optimization Methods (4 papers). Sergey Shebalov is often cited by papers focused on Supply Chain and Inventory Management (7 papers), Transportation Planning and Optimization (4 papers) and Vehicle Routing Optimization Methods (4 papers). Sergey Shebalov collaborates with scholars based in United States and Türkiye. Sergey Shebalov's co-authors include Diego Klabjan, Richard Ratliff, Guillermo Gallego, John-Paul Clarke, Ellis L. Johnson, Xiaodong Luo and Fikri Karaesmen and has published in prestigious journals such as SHILAP Revista de lepidopterología, Operations Research and Mathematical Programming.

In The Last Decade

Sergey Shebalov

10 papers receiving 325 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Sergey Shebalov United States	7	161	115	111	101	82	11	347
Rodrigo Acuña-Agost France	9	136 0.8×	111 1.0×	39 0.4×	113 1.1×	51 0.6×	17	377
Ellis Johnson United States	10	260 1.6×	118 1.0×	57 0.5×	98 1.0×	18 0.2×	15	414
Anne Lange Germany	9	74 0.5×	73 0.6×	129 1.2×	60 0.6×	15 0.2×	22	345
Manoj Lohatepanont Thailand	5	240 1.5×	226 2.0×	45 0.4×	147 1.5×	8 0.1×	11	405
Chiwei Yan United States	9	97 0.6×	48 0.4×	28 0.3×	76 0.8×	160 2.0×	23	471
Raja G. Kasilingam Canada	13	371 2.3×	93 0.8×	276 2.5×	12 0.1×	45 0.5×	27	596
Yuh‐Horng Wen Taiwan	9	48 0.3×	115 1.0×	30 0.3×	60 0.6×	8 0.1×	16	385
Alp Muharremoglu United States	10	74 0.5×	31 0.3×	292 2.6×	39 0.4×	72 0.9×	15	387
Kuancheng Huang Taiwan	12	192 1.2×	57 0.5×	90 0.8×	7 0.1×	27 0.3×	21	321
Robert E. Caves United Kingdom	11	55 0.3×	211 1.8×	19 0.2×	171 1.7×	7 0.1×	25	372

Countries citing papers authored by Sergey Shebalov

Since Specialization

Citations

This map shows the geographic impact of Sergey Shebalov'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 Sergey Shebalov with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sergey Shebalov more than expected).

Fields of papers citing papers by Sergey Shebalov

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Sergey Shebalov. 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 Sergey Shebalov. The network helps show where Sergey Shebalov may publish in the future.

Co-authorship network of co-authors of Sergey Shebalov

This figure shows the co-authorship network connecting the top 25 collaborators of Sergey Shebalov. A scholar is included among the top collaborators of Sergey Shebalov 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 Sergey Shebalov. Sergey Shebalov is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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11 of 11 papers shown

Shebalov, Sergey, et al.. (2021). Machine learning approach to market behavior estimation with applications in revenue management. Journal of Revenue and Pricing Management. 20(3). 344–350. 6 indexed citations

Luo, Xiaodong, et al.. (2020). Variable pricing: an integrated airline pricing and revenue management model. Journal of Revenue and Pricing Management. 19(6). 421–435.

Klabjan, Diego, et al.. (2016). Itinerary-based nesting control with upsell. Journal of Revenue and Pricing Management. 15(2). 107–137. 1 indexed citations

Shebalov, Sergey, et al.. (2015). Lifting for mixed integer programs with variable upper bounds. Discrete Applied Mathematics. 186. 226–250. 1 indexed citations

Klabjan, Diego, et al.. (2014). Attractiveness-Based Airline Network Models with Embedded Spill and Recapture. SHILAP Revista de lepidopterología. 4(1). 9 indexed citations

Gallego, Guillermo, Richard Ratliff, & Sergey Shebalov. (2014). A General Attraction Model and Sales-Based Linear Program for Network Revenue Management Under Customer Choice. Operations Research. 63(1). 212–232. 112 indexed citations

Clarke, John-Paul, et al.. (2012). An Optimization Approach to Airline Integrated Recovery. Transportation Science. 46(4). 482–500. 101 indexed citations

Gallego, Guillermo, Richard Ratliff, & Sergey Shebalov. (2011). A general attraction model and an efficient formulation for the network revenue management problem. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 20 indexed citations

Shebalov, Sergey. (2009). Practical overview of demand-driven dispatch. Journal of Revenue and Pricing Management. 8(2-3). 166–173. 8 indexed citations

10.

Shebalov, Sergey & Diego Klabjan. (2006). Robust Airline Crew Pairing: Move-up Crews. Transportation Science. 40(3). 300–312. 83 indexed citations

11.

Shebalov, Sergey & Diego Klabjan. (2005). Sequence Independent Lifting for Mixed Integer Programs with Variable Upper Bounds. Mathematical Programming. 105(2-3). 523–561. 6 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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