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Achieve greater efficiency in areas like supply chain, energy, finance, mobility, and marketing with the integrated technology of Mathematical Optimization and Artificial Intelligence (MOAI).
Why we stand out
Machine learning (broadly speaking, artificial intelligence) and optimization have played crucial roles in analytics. Because machine learning is often used in predictive analytics and optimization in prescriptive analytics, simply predicting and then optimizing is sometimes referred to as "integration." However, the true integration of machine learning and mathematical optimization is much broader.
We have named this rapidly developing field of integration over the past few years MOAI (Mathematical Optimization + Artificial Intelligence), and we have established new technologies that surpass past research for those aspects that we consider practically effective. This has made it possible to rapidly solve complex and large-scale problems that could not be solved by traditional optimization or machine learning alone. To provide solutions using this new technology, we have established MOAI Lab.
MOAI Platform
We offer a platform capable of handling problems that are difficult to solve with specific optimization solvers.
Just as the "no free lunch theorem" exists in search algorithms, there's no universal algorithm for optimization problems. Even the problem class BQP, which is expected to be solved quickly by quantum computers in optimization, does not (or has not been proven to) include optimization problem classes (NP-complete, NP-hard).
Moreover, there are many practical algorithms other than mathematical optimization solvers (Gurobi, CBC, CPLEX, etc.), and these are mainly used to solve problems that mathematical optimization solvers are not good at. Choosing the right algorithm is essential for solving real-world challenges.
Optimization Solutions
As professionals in the application of optimization technologies, we leverage our extensive experience in solving various large-scale optimization problems to deliver the optimal solution.
Modeling is an extremely important process, to the point where it's often said that "80% of optimization project success is modeling, and 20% is algorithms." While the MOAI platform makes it easy to select the right algorithm, if you can't design a good model, you often won't be able to solve the problem, no matter how high-performance the software you use.
This process may seem simple at first glance, but it requires a combination of practical understanding, knowledge of optimization theory and applications, programming skills, and consulting ability to make practical proposals. Common failures include defining the requirements but being unable to solve the optimization problem, or obtaining some kind of result but it being impractical and ineffective.
As a professional team specializing in optimization applications, we possess all the necessary capabilities to solve our clients' challenges and propose optimization solutions that reliably deliver results.
Plans and Pricing
Available as a cloud service, via API, or for on-premise deployment.
We offer multiple plans to accommodate businesses of all sizes. Please contact us for details.
Our Team
Koji Nonobe
Representative Director CEO
Professor, Hosei University
Ph.D. (Informatics), Kyoto University
Developer of scheduling optimization solvers and constraint optimization solvers. Algorithms developed have been incorporated into major commercial optimization solvers. Extensive experience solving real-world large-scale optimization problems through joint research with corporations.
Mikio Kubo
Director CTO
Professor, Tokyo University of Marine Science and Technology
Ph.D. (Engineering), Waseda University
Advisor at Optimind, Director at A* Quantum.
A leading expert in optimization applications, actively engaged in research and application of supply chain optimization using mathematical methods such as mathematical optimization and machine learning. Has provided technical support to numerous optimization projects for major corporations for over 30 years. Author of over 50 books on supply chain and optimization.
Kazuhiro Kobayashi
Director
Associate Professor, Aoyama Gakuin University
Ph.D. (Science), Tokyo University of Science
He has a track record of joint research with multiple companies, including major manufacturers and logistics companies, in the application of optimization technology. In the past, he worked at a major company developing systems and at the National Maritime Research Institute (a national research institute) engaged in a national project for logistics research.
Tsutomu Saito
Director
B-Proud Co., Ltd. / Toyota Motor Corporation
Previously, at Kozo Keikaku Engineering Inc., he was a core member of optimization algorithm development for many years, solving numerous real-world problems. He is currently involved in optimization projects at Toyota Motor Corporation.
Jinhua Zheng
Director
Has been engaged in optimization-related consulting for over 10 years. Participated in multiple large-scale optimization projects. Fluent in four languages.
Wu Wei
Assistant Professor, Shizuoka University
Ph.D. (Information Science)
Awarded numerous academic prizes during his student years. Involved in joint research with many companies in scheduling optimization, financial optimization, and other areas.
Nobuyuki Tsuchimura
Education and Technology Staff, Kwansei Gakuin University, Ph.D. (Engineering)
Graduated from Kyoto University. After serving as an Assistant Professor at the University of Tokyo, he holds his current position. Active in open-source software development. The character code extension (UTF-8 support) for Japanese pLaTeX, which he developed while participating in the "Strategic Software Creation Human Resource Development Program" at the University of Tokyo, is widely used.
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