Evaluate the objective function (average vehicle speed) using traffic simulation by MAS!
We would like to introduce the "Signal Control Optimization through Black Box Optimization" using Fixstars Amplify, which we handle. In this sample code, we implement optimal control of traffic lights to maximize the average speed of all vehicles traveling in the city. It is also believed that optimization can be achieved similarly even when using the average vehicle speed observed from actual traffic conditions or the number of vehicles entering a specific intersection per unit time as the objective function. [Contents] ■ MAS for Urban Traffic Congestion ■ Implementation of FMQA Program (Integer Input Values) ■ Optimization of Traffic Light Control through Black Box Optimization ■ Summary and Guidelines for Practical Operation *For more details, please refer to the related links or feel free to contact us.
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With over 700 companies and organizations utilizing it, and more than 50 million cumulative executions, our optimization computing cloud service powered by cutting-edge quantum technology and other advanced computing methods supports the optimization and automation of our customers' operations. The optimization computing cloud service "Fixstars Amplify" is used in on-site management planning tasks such as production planning, shift scheduling, vehicle dispatch planning, and delivery planning. It can also be utilized for optimizing shelf layouts in automated warehouses and for automatic control of AGVs as a digital twin. In research and development, its use is expanding in areas such as materials informatics and optimization of design parameters. With the world's best service for solving social issues, the highest precision and efficiency, and the most user-friendly optimization computing cloud service, along with comprehensive support from excellent optimization consultants, we provide total support for the optimization of various operations in the manufacturing industry. 【Usage Applications】 Production planning, shift planning, equipment investment optimization, optimal routing for AGVs, shelf layout optimization in automated warehouses, vehicle dispatch planning, delivery planning, design parameter optimization, materials informatics, etc.