Solving complex optimization problems with evolutionary computation.
Information and Communication Technology (Saitama University Research Seed Collection 2025-27 p.89)
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.
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Tomohiro Harada, Associate Professor Graduate School of Science and Engineering, Department of Mathematical and Electronic Information, Information Area 【Recent Research Themes】 ● Evolutionary computation utilizing machine learning for high-value cost optimization problems ● Acceleration of evolutionary computation algorithms using parallel computing ● Multi-objective optimization using multi-objective evolutionary computation
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【Appeal Points to the Industry】 ● Proposing methods for applying evolutionary computation algorithms tailored to optimization targets ● Providing consistent support from the planning to the implementation of optimization applications ● Numerous awards in optimization competitions in the industry ● Possessing advanced technologies for multi-objective optimization and constrained optimization 【Examples of Practical Applications】 ● Optimization of hybrid rocket engine design ● Signal control scheduling using traffic simulators
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Examples of multi-objective optimization problems
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The Saitama University Open Innovation Center is a center that functions as a liaison office for industry-academia-government collaboration. It consists of three departments: the Industry-Academia-Government Collaboration Department, the Intellectual Property Department, and the Startup Support Department, each staffed with coordinators well-versed in various fields. The center's activities include solving technical challenges in companies, supporting the implementation of joint research, and conducting technology transfer aimed at introducing and utilizing Saitama University's intellectual property.