Optimization and Mathematical Programming
Optimization and Mathematical Programming is a research topic within Control and Systems Engineering. Science Explorer counts 18k research works in it since 1953. 24.7% of them reached the world's top 10% most cited for their field and year.
This cluster of papers focuses on the optimization of multi-objective transportation problems, particularly in the context of supply chain management and aggregate production planning. It explores the application of fuzzy goal programming, genetic algorithms, and metaheuristic approaches to address challenges such as fixed charge transportation, sustainable development, and uncertainty in decision-making. The research also delves into techniques like linear fractional programming and intuitionistic fuzzy logic to enhance the efficiency and robustness of transportation problem solutions.
- Fuzzy Goal Programming
- Aggregate Production Planning
- Multi-Objective Optimization
- Fixed Charge Transportation Problem
- Genetic Algorithm
- Linear Fractional Programming
- Intuitionistic Fuzzy
- Supply Chain Management
- Sustainable Development
- Metaheuristic Algorithms
- Research works
- 18k fractional, since 1953
- In the world top 10%
- 4.5k per year above
- Top-10% rate
- 24.7% share of its works in the world top 10%
- Growth, 2013–17 → 2018–22
- +36% the tick is no change
Which countries lead Optimization and Mathematical Programming research?
By volume, India and China publish the most (591 and 436 works in 2022–2025).
By volume, 2022–2025
- 1 India 591 works
- 2 China 436 works
- 3 Indonesia 278 works
- 4 Türkiye 189 works
- 5 Iran 166 works
- 6 United States 163 works
- 7 Pakistan 117 works
- 8 Saudi Arabia 71 works
- 9 Brazil 66 works
- 10 Iraq 62 works
How concentrated that is
The same countries as shares of everything the list above accounts for. A node where two countries do two thirds of the work and one spread evenly across twelve read alike as a ranking and not at all alike here.
Shares of the rows listed above, not of the whole node.
Which institutions lead Optimization and Mathematical Programming research?
By volume in 2022–2025, Vellore Institute of Technology University publishes the most Optimization and Mathematical Programming research, followed by SRM Institute of Science and Technology and Vidyasagar University.
By volume, 2022–2025
- 1 Vellore Institute of Technology University India 31 works
- 2 SRM Institute of Science and Technology India 24 works
- 3 Vidyasagar University India 22 works
- 4 University of the Punjab Pakistan 18 works
- 5 Universitas Sumatera Utara Indonesia 16 works
- 6 Thapar Institute of Engineering & Technology India 16 works
- 7 Istanbul Technical University Türkiye 13 works
- 8 International Islamic University, Islamabad Pakistan 13 works
- 9 Yıldız Technical University Türkiye 13 works
- 10 Riphah International University Pakistan 12 works
Who are the leading researchers in Optimization and Mathematical Programming?
The most-cited researchers publishing on Optimization and Mathematical Programming include Kalyanmoy Deb, Witold Pedrycz and W. W. Cooper.
- 1 Kalyanmoy Deb 6.7k citations
- 2 Witold Pedrycz 5.4k citations
- 3 W. W. Cooper 4.6k citations
- 4 A. Charnes 4.5k citations
- 5 Ronald R. Yager 4.2k citations
- 6 Enrique Herrera‐Viedma 3.3k citations
- 7 Zeshui Xu 3.3k citations
- 8 Gwo‐Hshiung Tzeng 2.6k citations
Ranked by citations received across their whole record, among researchers with at least three works on this topic.
Where is Optimization and Mathematical Programming research done?
The largest centres of Optimization and Mathematical Programming research in 2022–2025 are Istanbul (Türkiye), Tehran (Iran), Chennai (India) and Beijing (China). Among places with at least 20 works in it, it is an unusually large share of all research in Medinīpur.
Largest cities, 2022–2025
Where it is the local speciality
- MedinīpurIN · 23.7 works76×
Location quotient: how much more of its research is in Optimization and Mathematical Programming than the world average.
Where is the best place to study Optimization and Mathematical Programming?
Among universities, judged by research, University of the Punjab, Riphah International University and Vidyasagar University score highest, combining excellence, specialisation, size, growth and international reach. Research strength is one signal when choosing where to study; it does not measure teaching.
One dot per university in the table below. The upper left is the interesting corner: small places doing unusually strong work.
| # | University | Score | Top 10% | Specialisation | Works | Growth |
|---|---|---|---|---|---|---|
| 1 | University of the Punjab Pakistan | 78.6 | 59.4% | 20.5× | 18 | — |
| 2 | Riphah International University Pakistan | 74.5 | 61.1% | 28.8× | 12 | — |
| 3 | Vidyasagar University India | 71.2 | 42.9% | 88.3× | 22 | +94.4% |
| 4 | Vellore Institute of Technology University India | 67.3 | 10.7% | 10.3× | 31 | +194.8% |
| 5 | International Islamic University, Islamabad Pakistan | 66.7 | 44.3% | 37.7× | 13 | — |
| 6 | Istanbul Technical University Türkiye | 63.6 | 38.8% | 12.3× | 13 | +85.7% |
| 7 | King Abdulaziz University Saudi Arabia | 60.6 | 30.4% | 7.0× | 12 | +273.8% |
| 8 | Thapar Institute of Engineering & Technology India | 59.2 | 29.7% | 33.3× | 16 | +66.0% |
| 9 | Qassim University Saudi Arabia | 57.3 | 31.4% | 10.7× | 8 | — |
| 10 | Yıldız Technical University Türkiye | 54.8 | 18.6% | 16.1× | 13 | +139.5% |
Universities only. Score blends excellence (30%), specialisation (25%), size (20%), growth (15%) and international reach (10%), 2015–2022; growth compares 2010–14 with 2015–19.
Is Optimization and Mathematical Programming research growing?
Output in 2018–2022 was 36% higher than in 2013–2017, peaking in 2021. The fastest-growing topics are Optimization and Mathematical Programming.
The same series as a ribbon — one cell per year, darker for more. The line above answers how much; this answers when.
Which topics inside it are moving
Growth and decline on one axis around a shared zero. Two lists side by side hide the thing that matters: whether the growth dwarfs the decline, or the other way round.