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Logistics operations require continuous improvement in daily operational productivity to promote white logistics. In recent years, approaches using AI to determine delivery routes have gained attention, but incorporating various conditions such as stacking methods based on products and driver skills makes calculations difficult, leading to variations in planning accuracy. The method of finding optimal solutions from a vast number of patterns that consider these many conditions is called "combinatorial optimization problems," which are addressed in logistics operations through themes such as loading, shifts, and route optimization. A technology that is gaining attention as a solution to this is "quantum computing." By utilizing the "MAGELLAN BLOCKS" quantum computing solution provided by GrooveNotes, it has been confirmed that delivery efficiency can be improved by over 50% in verifications with major delivery companies. Additionally, there are various cases in internal logistics, transportation between bases, and last-mile delivery, contributing to logistics cost improvements ranging from tens of millions to hundreds of millions of yen annually, as well as reductions in CO2 emissions, by maximizing loading rates, reducing the number of trucks, leveling cargo volumes, and improving turnover rates.

• Logistics and warehouse management systems

In today's rapidly changing market and customer needs, production and manufacturing sites are required to improve productivity more than ever. However, even in production scheduling, intricate designs are necessary for order and equipment allocation, and there are limits to how much skilled workers can manually create and modify plans in response to fluctuations in demand forecasts and production capacity. The latest technology that excels in planning production schedules and plans with such complex constraints is quantum computing. By utilizing the "MAGELLAN BLOCKS" quantum computer solution provided by GrooveNotes, it is possible to automatically derive the optimal plans, such as the work sequence that minimizes setup changes according to various manufacturing items and the allocation of tools considering the workers' dominant hands. This enables the reproduction and enhancement of judgments made by skilled workers, which was difficult to achieve with traditional systems. There are also cases where planning tasks that previously took more than half a day to complete manually can now be finished in less than an hour, demonstrating efforts toward business automation. We will introduce examples of the use of quantum computers in manufacturing sites.

• Process Control System

Instantly explore the desired information from documents that describe know-how and use cases practiced by predecessors, which are complex and cannot be simply judged based on rules (including regulations, as legal documents can have varying interpretations). The document search solution "MAGELLAN BLOCKS," independently developed using advanced natural language processing technology, vectorizes the characteristics of entire sentences rather than just the words. This enables the quick identification of semantically similar sentences in response to inquiries. Questioners can simply ask questions in natural language that they use daily, allowing them to search for appropriate answers. *For more details, please download the PDF or feel free to contact us.*

• Database

As a challenge in logistics, not only logistics operators but also shippers such as manufacturers, trading companies, wholesalers, retailers, and transportation and warehousing must overcome significant issues such as labor shortages, deteriorating working conditions, and rising costs... One method to achieve this is to eliminate waste in resources while maintaining and improving service quality, thereby establishing efficient and effective delivery— the key to the solution lies in realizing optimization through the use of quantum computers. The world's first quantum computer-equipped "MAGELLAN BLOCKS" can derive the optimal solution for desired combination patterns instantly by simply inputting operational constraints, without requiring difficult specialized knowledge or programming skills. ◆◇Case Study: Mitsubishi Estate Co., Ltd.◇◆ Mitsubishi Estate conducted Japan's first verification using AI and quantum computers to derive efficient routes for waste collection and transportation for 26 buildings it owns in Marunouchi, Tokyo. It predicted waste generation with approximately 94% accuracy and, based on that, derived the optimal collection route from a vast number of combinations. As a result, it confirmed estimates that CO2 emissions would be reduced by approximately 57% and the number of vehicles by about 59%, contributing to SDGs and decarbonization efforts.

• Logistics and warehouse management systems