Workshop Topic
Combinatorial optimization is at the core of many intelligent decision-making problems, including routing, scheduling, resource allocation, robotics, logistics, and circuit routing. As real-world systems become larger, more dynamic, and more uncertain, traditional optimization methods face increasing challenges in scalability, adaptability, and long-term deployment.
CICOW 2026 focuses on the intersection of Computational Intelligence (CI) and Combinatorial Optimization (CO). The workshop aims to explore how evolutionary computation, machine learning, reinforcement learning, and large language models can support the design of more adaptive, efficient, and practical optimization methods.
By bringing together researchers from artificial intelligence, computational intelligence, machine learning, and operations research, this workshop provides a forum for discussing both theoretical advances and real-world applications of intelligent optimization.
Objectives and Scope
The objective of CICOW 2026 is to promote discussion on computational intelligence methods for solving complex combinatorial optimization problems. We are particularly interested in methods that address practical challenges such as large-scale search spaces, dynamic environments, uncertainty, multiple high-quality solutions, and lifelong optimization.
The workshop will feature invited talks covering algorithm design, learning-assisted optimization, hybrid methods in computational intelligence and operations research, theoretical analysis, benchmark studies, and applications in real-world systems. We also encourage discussions that bridge academic research and industrial needs, especially in logistics, transportation, robotics, electronics, energy systems, and intelligent manufacturing.
Scope and Topics
Topics of interest include, but are not limited to:
- Computational intelligence for combinatorial optimization
- Evolutionary computation for routing, scheduling, and resource allocation
- Machine learning, reinforcement learning, and large language models for optimization
- Learning-assisted algorithm design and automated heuristic generation
- Hybrid computational intelligence and operations research methods
- Dynamic, uncertain, multimodal, and lifelong combinatorial optimization
- Benchmarking, evaluation, and generalization of optimization algorithms
- Real-world applications in low-altitude intelligent systems, logistics, transportation, robotics, electronic design automation, electronics, and energy systems
Participation
CICOW 2026 is planned as a half-day invited-talk workshop. The program will feature invited presentations by researchers and practitioners from academia and industry working on computational intelligence, combinatorial optimization, machine learning, operations research, and real-world optimization applications.
Researchers and industry practitioners interested in sharing related work are welcome to contact the organizers with a brief expression of interest, including their name, affiliation, tentative talk title, and a brief bio.
Please note that CICOW 2026 does not plan to organize an open call for paper submissions at this stage.
Workshop Co-Chairs
For questions about the workshop or expression of interest, please contact the workshop co-chairs.