Gajanan Waghmare

604 total citations
9 papers, 454 citations indexed

About

Gajanan Waghmare is a scholar working on Computational Theory and Mathematics, Artificial Intelligence and Mechanical Engineering. According to data from OpenAlex, Gajanan Waghmare has authored 9 papers receiving a total of 454 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Computational Theory and Mathematics, 4 papers in Artificial Intelligence and 3 papers in Mechanical Engineering. Recurrent topics in Gajanan Waghmare's work include Advanced Multi-Objective Optimization Algorithms (5 papers), Metaheuristic Optimization Algorithms Research (4 papers) and Evolutionary Algorithms and Applications (3 papers). Gajanan Waghmare is often cited by papers focused on Advanced Multi-Objective Optimization Algorithms (5 papers), Metaheuristic Optimization Algorithms Research (4 papers) and Evolutionary Algorithms and Applications (3 papers). Gajanan Waghmare collaborates with scholars based in India. Gajanan Waghmare's co-authors include R. Venkata Rao and В. Д. Калыанкар and has published in prestigious journals such as Information Sciences, Applied Thermal Engineering and Applied Mathematical Modelling.

In The Last Decade

Gajanan Waghmare

9 papers receiving 433 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Gajanan Waghmare India	8	182	125	111	88	81	9	454
Emerson Hochsteiner de Vasconcelos Segundo Brazil	9	215 1.2×	170 1.4×	147 1.3×	45 0.5×	59 0.7×	14	485
Alexandru-Ciprian Zăvoianu Austria	10	125 0.7×	118 0.9×	116 1.0×	159 1.8×	115 1.4×	26	443
Yunlang Xu China	13	196 1.1×	110 0.9×	84 0.8×	118 1.3×	249 3.1×	36	532
Saeed Nezamivand Chegini Iran	10	191 1.0×	93 0.7×	162 1.5×	75 0.9×	252 3.1×	14	513
Koon Meng Ang Malaysia	8	245 1.3×	122 1.0×	32 0.3×	92 1.0×	90 1.1×	15	504
Radomil Matoušek Czechia	10	82 0.5×	72 0.6×	156 1.4×	100 1.1×	85 1.0×	39	447
Jean Bigeon France	10	91 0.5×	94 0.8×	100 0.9×	142 1.6×	87 1.1×	40	376
Lizhong Yao China	10	120 0.7×	81 0.6×	74 0.7×	41 0.5×	73 0.9×	42	358
Sew Sun Tiang Malaysia	11	157 0.9×	78 0.6×	58 0.5×	117 1.3×	72 0.9×	47	430
Prabhujit Mohapatra India	14	304 1.7×	181 1.4×	174 1.6×	92 1.0×	67 0.8×	34	629

Countries citing papers authored by Gajanan Waghmare

Since Specialization

Citations

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

Fields of papers citing papers by Gajanan Waghmare

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Gajanan Waghmare

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

All Works

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9 of 9 papers shown

Waghmare, Gajanan, et al.. (2022). Path synthesis of a four-bar linkage using a teaching-learning-based optimization algorithm. International Journal for Computational Methods in Engineering Science and Mechanics. 24(1). 40–51. 7 indexed citations

Rao, R. Venkata & Gajanan Waghmare. (2016). A new optimization algorithm for solving complex constrained design optimization problems. Engineering Optimization. 49(1). 60–83. 151 indexed citations

Rao, R. Venkata & Gajanan Waghmare. (2015). Design optimization of robot grippers using teaching-learning-based optimization algorithm. Advanced Robotics. 29(6). 431–447. 29 indexed citations

Rao, R. Venkata & Gajanan Waghmare. (2015). Optimization of thermal performance of a smooth flat-plate solar air heater using teaching–learning-based optimization algorithm. Cogent Engineering. 2(1). 997421–997421. 15 indexed citations

Rao, R. Venkata, В. Д. Калыанкар, & Gajanan Waghmare. (2014). Parameters optimization of selected casting processes using teaching–learning-based optimization algorithm. Applied Mathematical Modelling. 38(23). 5592–5608. 55 indexed citations

Rao, R. Venkata & Gajanan Waghmare. (2014). Complex constrained design optimisation using an elitist teaching-learning-based optimisation algorithm. 3(1). 81–81. 26 indexed citations

Rao, R. Venkata & Gajanan Waghmare. (2014). A comparative study of a teaching–learning-based optimization algorithm on multi-objective unconstrained and constrained functions. Journal of King Saud University - Computer and Information Sciences. 26(3). 332–346. 56 indexed citations

Rao, R. Venkata & Gajanan Waghmare. (2014). Multi-objective design optimization of a plate-fin heat sink using a teaching-learning-based optimization algorithm. Applied Thermal Engineering. 76. 521–529. 45 indexed citations

Waghmare, Gajanan. (2012). Comments on “A note on teaching–learning-based optimization algorithm”. Information Sciences. 229. 159–169. 70 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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