- 2024 Edition
Did you know that annealing machines are already being used in business, not just for verification, but as a means to solve real-world problems? This article will cover examples of applications that have been published so far. The word "application" means to apply, and it refers to a method of applying technology to solve a real problem, which is also used in the form of a smartphone application. Knowing what real-world business problems are being handled as combinatorial optimization problems and delivering results is an important input for knowing how to use an annealing machine for your own problem solving.
At the Port of Los Angeles, said to be the busiest port in the U.S., huge cranes called RTGs (Rubber Tired Gantry cranes) move containers of products delivered by ocean freight to their proper locations and unload them. A number of transport trucks spend their waiting time at the port to bring the desired cargo to its destination.
One of the vendors has achieved significant results by using quantum annealing to minimize truck waiting times -- this is one of the most prominent examples of D-Wave utilization. In this case, in addition to customizing the package software, the vendor was able to reduce truck waiting time and, as a result, doubled the amount of cargo taken out of the truck.*1
A major IT equipment maintenance company in Japan applied Annealing to their planning of delivery plans for parts from parts centers in response to breakdowns and other problems. They reported that they succeeded in reducing the time required to create a plan to just 12 minutes, one-tenth of the previous time.*2
In the latter case, depending on the occurrence of the breakdown, various constraints must be taken into account, such as traffic conditions at the time, the transportation vehicle, and the type of parts required, and it is thought that several problems are compounded, including not only route selection but also the combination of parts selection for loading and time combinations.
In logistics and transportation, this mix of several types of optimization problems can become very complex when their combination is considered.
The Port of Los Angeles case study reveals that while there were many things to optimize, they defined truck waiting time as a Key Performance Indicator (KPI) and worked to minimize it. In addition to optimization using an annealing machine, they also changed the way containers are placed, and made modifications to the reservation system, etc., to improve overall operational efficiency. In this way, we expect to see more and more efforts to incorporate annealing machines as part of the overall system to increase overall efficiency.
Work shift is an area where optimization process with annealing machines is expected to be effective. The nature of the business or operation, the service specifications, the size of the office, and various other conditions will determine the constraints of the optimization problem.
In an example of using an annealing machine to automatically create work shifts for support contact center staff, it was possible to reduce the time required to create shifts by more than 50%, and a survey of staff members regarding this trial showed that more than 90% of them had a positive opinion. *3
In a large call center for financial institutions, it has been shown that using an annealing machine for shift scheduling can reduce surplus staffing, which should have originally been unnecessary, by 80%. As a result, consideration is being given to actually using annealing in business operations. *4
In large call centers, not only are the constraints complex, but the excess caused by the way shifts are organized can also be a major cost. Call centers are believed to be a field which can effectively demonstrate the cost effectiveness of using Annealing machines.
At the research institute of Hitachi Ltd., researchers' work shifts were created using annealing prior to the above-mentioned case. *5
Some industries and offices are difficult to represent with Ising models and constraint formulas due to various unique conditions, or the staff size may not be so large. Therefore, shift optimization solutions using various methods such as software applications and mathematical optimization solvers, as well as annealing, are becoming increasingly popular.
In addition to work shifts, annealing has also been applied to production processes and other operations related to scheduling.
In a successful case of applying annealing to the planning of printing process planning, the creation of a printing process schedule used to take longer than a whole night, but by applying annealing, the time required could be reduced to only one hour. *6
This is a very unique case where a well-known printing company has achieved the development and practical application of annealing software.
Applications to the financial sector are also flourishing. A case study of the application of an annealing machine to a large-scale and complex non-life insurance portfolio optimization problem in the non-life insurance underwriting business, which involves both risk-taking such as catastrophes and stable profitability, is presented in detail on this website.
On the other hand, in the same financial business, there have been some cases presented where annealing machines have been successfully used to create low-risk portfolios in the investment field, such as stocks, and are now being put into practical use. *7
In insurance, which is the social infrastructure for disaster preparedness, as well as in investment products such as stocks, portfolio optimization is required to minimize risk and maximize returns.
In addition, the annealing machine is being used to detect and eliminate mispricing in High-Frequency Trading (HFT) by integrating an annealing machine with the proprietary technology of HFT providers, and verification is being conducted in the actual financial market. *8
In HFT, this is an area where the high speed of annealing machines is even more likely to prove effective than in other investment areas. Compared to the problem of finding the work shift or the shortest path, investment work is a world that is difficult to understand without deep expertise. Annealing machines that do not depend on people's psychological fluctuations may become the key to the market. Why not learn about investments to learn about annealing machines?
Do you know that quantum annealing is being applied to optimize TV commercial distribution plans? In this case, in order for as many people as possible to see a variety of commercials without bias, there is the problem of the combination of which broadcaster, which time slot, and which commercial to air, which has already been optimized by quantum annealing. *9
It is a surprise to learn that the TVs that many people watch in their daily lives and the commercials that are broadcast on them may actually be optimized by an annealing machine, and conversely, it is an example of how combinatorial optimization is so close at hand, even if the users are unaware of it.
These are examples of annealing applications that have already been put to practical use, divided into categories with similar purposes to be optimized. There are so many optimization problems in the case of logistics and transportation planning, which consists of a wide variety of operations such as procurement, warehousing, manufacturing, and transportation, that the first issue would be to decide "what do we want to optimize," or "what is its KPIs? The shift optimization problem is nothing more than creating a shift, but the constraints and problem size vary from business to business. Portfolio optimization problems in the financial field are optimization problems of invisible phenomena for us. However, the gains and losses that the solution yields have a tremendous impact on our lives. Investment activities are greatly influenced by economic trends. In the case of ad serving optimization, even if we do not know that the optimization process is taking place behind the scenes, we are part of the economic activity by seeing it.
There are many other examples, including those in the verification phase, that have achieved surprisingly high results. The knowledge of engineers and business people who use annealing machines is the key to actually applying them to social issues and operating them as services. By accumulating technology through the emergence of as many use cases as possible, solutions can be built to optimize what is necessary and reduce the cost of problem-solving.