Solving complex optimization problems with evolutionary computation.
Keywords: Evolutionary computation, optimization, artificial intelligence, multi-objective optimization
There are many problems around us that require finding the optimal answer. For example, route planning for deliveries, scheduling work in factories, and designing the structure of automobiles are some of them. To solve these "optimization problems," I am researching a type of artificial intelligence technology called evolutionary computation. Evolutionary computation mimics the mechanisms of biological evolution to find excellent answers through trial and error. It has the strength of being able to solve complex optimization problems, which are difficult to tackle with mathematical approaches, with high precision and in a general manner. I am studying methods to find optimal answers more efficiently by accelerating evolutionary computation using parallel computing and by combining evolutionary computation with machine learning. Additionally, I am working on research to develop algorithms that efficiently seek solutions for multi-objective optimization problems, where there are multiple goals.
- Company：埼玉大学 オープンイノベーションセンター
- Price：Other
