Inspiration
Modern shipyards handle thousands of large blocks that must be packed, moved, and scheduled efficiently. Small improvements in planning can save significant time and resources. The Optimization Grand Challenge 2026 inspired Team SUN to explore intelligent optimization techniques for solving complex shipyard logistics problems.
What it does
OptiSUN aims to develop an optimization algorithm that improves block packing and scheduling decisions under real-world operational constraints. The project focuses on maximizing efficiency, reducing delays, and improving resource utilization.
How we plan to build it
Our approach will involve studying optimization techniques, heuristic methods, and algorithmic strategies. We plan to analyze the competition datasets, design efficient search and scheduling methods, and evaluate performance using the competition scoring system.
Challenges
The challenge involves handling large-scale combinatorial optimization problems with strict constraints and time limitations. Finding high-quality solutions while maintaining computational efficiency is expected to be one of the most difficult aspects of the project.
What we learned
Through this challenge, we aim to strengthen our knowledge of optimization, algorithm design, operations research, and real-world industrial problem solving.
Future Improvements
As the project develops, we plan to explore advanced optimization techniques, hybrid algorithms, and AI-assisted decision-making methods to further improve performance.
Log in or sign up for Devpost to join the conversation.