Rajesh Piplani

54 papers receiving 1.5k citations

Hit Papers

Deep reinforcement learning for dynamic scheduling of a f...2022202620232024202250100150

Peers

Rajesh Piplani
Comparison fields: 5 of 83
  • Management Information Systems 696
  • Industrial and Manufacturing Engineering 681
  • Strategy and Management 604
  • Management Science and Operations Research 264
  • Control and Systems Engineering 121
Replace Anders Segerstedt with:
Anders Segerstedt Sweden
Bernard Grabot France
Jei‐Zheng Wu Taiwan
Enzo Morosini Frazzon Brazil
M.I.M. Wahab Canada
Seyed Hessameddin Zegordi Iran
Carlos Julio Vidal Holguín Colombia
Rainer Lasch Germany
S. Viswanathan Singapore
Rajesh Piplani relative to Anders Segerstedt Sweden Anders Segerstedt's profile →
Citations per field
00.5×3.6×
Anders Segerstedt · 1×
Citations per year

Countries citing papers authored by Rajesh Piplani

Since Specialization
Citations

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

Fields of papers citing papers by Rajesh Piplani

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Rajesh Piplani

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

All Works

20 of 20 papers shown
#WorkIndexed citations
1 2
2 1
3 12
4
Deep reinforcement learning for dynamic scheduling of a flexible job shopbreakdown →
177
5 5
6 32
7 13
8 37
9 1
10 8
11 14
12 32
13 21
14 1
15 84
16 7
17 2
18 214
19 15
20 12

About Rajesh Piplani

Rajesh Piplani is a scholar working on Management Information Systems, Industrial and Manufacturing Engineering and Strategy and Management, having authored 55 papers that have together received 1.6k indexed citations. Recurring topics across this work include Scheduling and Optimization Algorithms (21 papers), Supply Chain and Inventory Management (20 papers) and Sustainable Supply Chain Management (15 papers). The work is most often cited by research in Management Information Systems (696 citations), Industrial and Manufacturing Engineering (681 citations) and Strategy and Management (604 citations). Rajesh Piplani has collaborated with scholars based in Singapore, United States and India. Frequent co-authors include S. Viswanathan, Carlos Toro, C.K.M. Lee, Shaligram Pokharel, G.H. Lim, Ratih Dyah Kusumastuti, Albert Tan, I Nyoman Pujawan, Saibal Ray and Jitamitra Desai. Their work appears in journals such as European Journal of Operational Research, International Journal of Production Economics and Journal of the Operational Research Society.

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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