Supply chain optimization using AI and mathematical optimization techniques.
Demand forecasting, production optimization, inventory optimization, delivery optimization, logistics network optimization, personnel allocation optimization, revenue optimization, and more are possible. 'SCMOPT ZERO' is an integrated optimization system that can provide fast and good answers even for large-scale problems by designing models and selecting algorithms (solvers) based on the correct methodology of supply chain optimization. It can consider various constraints of real-world problems, requires minimal parameter settings, and does not need corrections due to unsatisfactory results. Taking into account the overall objectives and constraints, it automatically calculates balanced and appropriate answers from a vast number of combinations. Additionally, by adopting carefully selected solvers and models, it is capable of solving problems of the largest scale that can be addressed with existing technologies. [Benefits] ■ Cost reduction ■ Supply chain resilient to environmental changes ■ Improved customer satisfaction and sales *For more details, please download the PDF or feel free to contact us.
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basic information
**Features** ■ Interface - A cloud-based service that allows direct use of Excel data (also compatible for on-premises use) ■ Functions - Capable of data analysis, forecasting, optimization, and visualization - Customization available as needed ■ Performance - Good results obtained from experiments with benchmark problems and real-world issues using high-performance algorithms and modeling ■ Data Integration - Integrated optimization possible through data linkage between SCMOPT systems - Integration with external systems via xlsx and API is also possible *For more details, please download the PDF or feel free to contact us.*
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For more details, please download the PDF or feel free to contact us.
Line up（5）
| Model number | overview |
|---|---|
| Scheduling Optimization Solver OptSeq | Solver for quickly solving large-scale scheduling optimization problems https://www.logopt.com/optseq/ |
| Delivery Optimization Solver METRO | Solver for quickly solving large-scale delivery optimization problems https://www.logopt.com/metrosolver/ |
| Set Covering Optimization Solver OptCover | Solver for quickly solving large-scale set covering problems https://www.logopt.com/optcover/ |
| Mathematical Optimization Solver Gurobi Optimizer | Fast mathematical optimization solver https://www.logopt.com/gurobi/ |
| Constraint Optimization Solver SCOP | Solver for quickly solving large-scale combinatorial optimization problems https://www.logopt.com/scop2/ |
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Company information
Our company was established in 1991 to provide the highest level of technology for optimization in logistics (supply chain). Since then, we have expanded the scope of our optimization solutions beyond the supply chain, and since around 2016, we have also been providing data analysis solutions using AI. We operate in Japan, China, and South Korea. With technical support from university professors who have extensive practical experience in the field of mathematical optimization both domestically and internationally, we develop products and provide services that enable us to solve difficult optimization problems that other companies cannot address, thus offering world-class optimization solutions.
![[Information] How the introduction of a scheduler changes production planning operations.](https://image.mono.ipros.com/public/product/image/2001633084/IPROS5258002008102188825.png?w=280&h=280)
![[Information] The Approach to Production Planning Varies by Site](https://image.mono.ipros.com/public/product/image/2111465/IPROS13314949555914945854.png?w=280&h=280)
