Qamar Askari
Impact in
- Artificial Intelligence top 2%
- Metaheuristic Optimization Algorithms Research
- Evolutionary Algorithms and Applications
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- Advanced Multi-Objective Optimization Algorithms
Papers in
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- Metaheuristic Optimization Algorithms Research 6
- Evolutionary Algorithms and Applications 1
- Neural Networks and Applications 1
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- Complexity and Algorithms in Graphs 1
- Advanced Multi-Objective Optimization Algorithms 1
- Journals
- Expert Systems with Applications (2 papers)Soft Computing (1 paper)Knowledge-Based Systems (1 paper)Neural Processing Letters (1 paper)
- Partner nations
- Pakistan
In The Last Decade
Qamar Askari
6 papers receiving 797 citations
Qamar Askari's Hit Papers
Peers
Comparison fields: 5 of 81
- Artificial Intelligence 547
- Computational Theory and Mathematics 251
- Energy Engineering and Power Technology 23
- Control and Systems Engineering 121
- Numerical Analysis 26
Countries citing papers authored by Qamar Askari
This map shows the geographic impact of Qamar Askari'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 Qamar Askari with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Qamar Askari more than expected).
Fields of papers citing papers by Qamar Askari
This network shows the impact of papers produced by Qamar Askari. 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 Qamar Askari. The network helps show where Qamar Askari may publish in the future.
Co-authors
The 2 scholars most cited alongside Qamar Askari, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Political Optimizer: A novel socio-inspired meta-heuristic for global optimization Hit paper breakdown → | 2020 | 470 |
| 2 | Heap-based optimizer inspired by corporate rank hierarchy for global optimization Hit paper breakdown → | 2020 | 312 |
| 3 | 2021 | 18 | |
| 4 | 2021 | 17 | |
| 5 | 2020 | 5 | |
| 6 | 2021 | 4 |
About Qamar Askari
Qamar Askari is a scholar working on Artificial Intelligence, Computational Theory and Mathematics, Management Science and Operations Research, Computer Networks and Communications and Biomedical Engineering, having authored 6 papers that have together received 826 indexed citations. Recurring topics across this work include Metaheuristic Optimization Algorithms Research (6 papers), Scheduling and Timetabling Solutions (2 papers), Evolutionary Algorithms and Applications (1 paper), Complexity and Algorithms in Graphs (1 paper), Advanced Multi-Objective Optimization Algorithms (1 paper), Vehicle Routing Optimization Methods (1 paper), Neural Networks and Applications (1 paper) and Optimization and Search Problems (1 paper). The work is most often cited by research in Artificial Intelligence (547 citations), Computational Theory and Mathematics (251 citations), Energy Engineering and Power Technology (23 citations), Control and Systems Engineering (121 citations) and Numerical Analysis (26 citations). Qamar Askari has collaborated with scholars based in Pakistan. Frequent co-authors include Irfan Younas and Mehreen Saeed. Their work appears in journals such as Expert Systems with Applications, Soft Computing, Knowledge-Based Systems and Neural Processing Letters.
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.