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Numerical Global Optimization Competition on GNBG–III Property Aware Test Suite

Deadline: 2026-03-31
Webpage: https://dsmlossf.github.io/GNBG-Competition-2026/

Description

This competition invites researchers to test their global optimization algorithms against a meticulously curated set of 24 problem instances from the Generalized Numerical Benchmark Generator (GNBG). The GNBG-III competition introduces the next generation of property-aware and computationally hard numerical benchmarks, designed to expose the behavior of global optimization algorithms under controlled structural conditions. The suite encompasses:
F1–F6: Foundational tests (smooth, analytic)
F7–F10: Coupled interactions evaluation
F11–F16: Multimodality and asymmetry
F17–F22: Hard static hybrids
F23–F24: Robustness and dynamic adaptation tracks
This competition challenges participants with diverse complexities such as varying modality, ruggedness, asymmetry, conditioning, variable interactions, basin linearity, and deceptiveness, offering a comprehensive evaluation of algorithmic performance. However, the focus goes beyond merely finding optimal solutions. It emphasizes understanding the process algorithms use to reach these solutions. Participants will explore how algorithms navigate deceptive landscapes, cross valleys, and adjust to the distinct difficulties of each problem instance. Ultimately, this is an opportunity to gain deeper insights into optimization within complex numerical environments. We warmly invite researchers to join this competition and put their global optimization algorithms to the test.

Abstract Submission

The competition allows 2-page contributions to the GECCO Companion to present short descriptions of the competition entry, focusing on algorithmic design, strengths and limitations. The 2-page abstract paper will require at least one author to register at the conference as a presenter. It is important to mention that these 2-page abstracts ARE NOT APC Eligible (no publication fee has to be paid by the authors) under the current ACM Open publishing guidelines. The following dates are relevant for these submissions:

  • Submission opening: April 1, 2026
  • Submission deadline: April 21, 2026
  • Notification: April 28, 2026
  • Camera-ready: May 5, 2026
  • Author's mandatory registration: May 11, 2026


Organizers

Rohit Salgotra

Rohit Salgotra is an Teach and Research Assistant Professor at the AGH University of Krakow in Poland. He specializes in Nature-Inspired Computing and has authored over 60 Science Citation Indexed (SCI) publications with a Google scholar citation of more than 2800 (h-Index: 29). Dr. Salgotra has been listed among Stanford University’s Top 2% Most Influential Scientists for the years 2021–2022, 2024 and 2025. Before joining AGH, he was a Research Officer at Swansea University, where he conducted studies on the socio-economic aspects of the COVID-19 pandemic. He was able to secure good amount of travel grants from various agencies including Science and Engineering Research Board (SERB), Council of Scientific and Industrial Research (CSIR), Govt. of India and IEEE, Computational Intelligence Society among others. Dr. Salgotra is an Academic Editor for "Mathematical Problems in Engineering" and a reviewer for several journals, including "IEEE Transactions on Evolutionary Computing" and "Swarm and Evolutionary Computing," among more than 30 other SCI journals.


Kalyanmoy Deb

Kalyanmoy Deb is Koenig Endowed Chair Professor at Department of Electrical and Computer Engineering in Michigan State University, USA. Prof. Deb's research interests are in evolutionary optimization and their application in multi-criterion optimization, modeling, and machine learning. He has been a visiting professor at various universities across the world including University of Skövde in Sweden, Aalto University in Finland, Nanyang Technological University in Singapore, and IITs in India. He was awarded IEEE Evolutionary Computation Pioneer Award for his sustained work in EMO, Infosys Prize, TWAS Prize in Engineering Sciences, CajAstur Mamdani Prize, Distinguished Alumni Award from IIT Kharagpur, Edgeworth-Pareto award, Bhatnagar Prize in Engineering Sciences, and Bessel Research award from Germany. He is fellow of IEEE, ASME, and three Indian science and engineering academies. He has published over 548 research papers with Google Scholar citation of over 149,000 with h-index 123. He is in the editorial board on 18 major international journals. More information about his research contribution can be found from https://www.coin-lab.org.


Amir H Gandomi

Amir H. Gandomi is internationally recognised as one of the world’s most highly cited and influential researchers, known for pioneering contributions to global optimisation, machine learning, big data analytics, and evolutionary computation. His work spans engineering, computer science, artificial intelligence, and data-driven modelling, and has shaped multiple research fronts worldwide.

He is an ARC DECRA Fellow and Professor of Data Science in the Faculty of Engineering and Information Technology at the University of Technology Sydney (UTS). Demonstrating exceptional research momentum, he was promoted to Full Professor only four years after completing his PhD, a distinction achieved by very few academics globally and reflecting his rapid and sustained international impact.

Professor Gandomi has received numerous prestigious honours acknowledging his contributions to science and engineering, including the 2024 IEEE TCSC Award for Excellence in Scalable Computing (MCR), the 2023 Achenbach Medal (bestowed at Stanford University), and the 2022 Walter L. Huber Prize, the highest-level mid-career research award in all areas of civil engineering. Most recently, he received the 2025 Sigma Xi Young Investigator Award from Sigma Xi, The Scientific Research Honor Society, one of the world’s oldest and most esteemed multidisciplinary academies, whose members include more than 200 Nobel Laureates such as Albert Einstein.

He has published more than 450 peer-reviewed journal articles and 14 books, collectively exceeding 74,000 citations (H-index=116). He has been repeatedly recognised as one of the world’s most influential scientific minds and a Highly Cited Researcher by Clarivate Analytics for six consecutive years. His global standing is further highlighted by his ranking as the 327th top computer scientist worldwide and 4th in Australia. In the most recent Stanford University–Elsevier analysis of the world’s most impactful researchers, he is ranked 29th internationally in the Artificial Intelligence and Image Processing subfield (2024).

Professor Gandomi holds editorial roles across several top-tier journals, including Associate Editor positions with IEEE Networks and IEEE Internet of Things Journal, and frequently serves as Editor and Guest Editor for leading outlets in artificial intelligence, optimisation, and computational engineering. He is also regularly invited to deliver keynote and plenary lectures at major international conferences and scientific forums.

Before joining UTS, he was an Assistant Professor at the School of Business at Stevens Institute of Technology in the United States, and a Distinguished Research Fellow at the BEACON Center at Michigan State University, an NSF-funded centre uniting biologists, engineers, and computer scientists to investigate and apply evolutionary principles to complex technological challenges.