News release overview
Hitachi develops CMOS annealing technology "relaxed MA" for supporting optimization tasks with continuous variables
Greater efficiency and precision in tasks such as reinsurance portfolio design in case of a large-scale disaster, or logistics planning
Tokyo, June 6, 2024 – Hitachi, Ltd. (TSE: 6501) has developed a new CMOS annealing technology, “relaxed MA,” capable of optimization calculation using continuous variables (any decimals between 0 and 1) *1 in addition to the binary variables (1 or 0) possible up to now, as a key technology for solving large-scale, complex problems of society. Support for continuous variables will make it possible to solve larger-scale combinatorial optimization problems*2 with high precision.
The effectiveness of the new technology was verified by applying it to a reinsurance portfolio optimization task*3 assuming a large-scale disaster with compound damage causes. The results confirmed the ability to perform detailed and high-precision portfolio calculation of the expected revenue amounts in 1 yen increments, for ten times as many insurance contracts as with earlier technology.
Hitachi plans to make use of this technology in other applications besides reinsurance portfolio design, including efficient power grid operation accounting for supply-demand balance, optimization of sales promotion measures in e-commerce, and improving efficiency of logistics planning, thereby contributing to the solution of various problems facing customers and society.
The results of this development project are to be presented in part at Adiabatic Quantum Computing (AQC) 2024, being held in Glasgow, UK from June 10 to 14, 2024.
Figure 1. Effectiveness for reinsurance portfolio optimization
(when expressing percentage of contracts held to three significant decimal figures)
*1 Continuous variable: A variable that differs from a binary variable, expressed by 0 or 1 only, in being able to represent 32-bit or 64-bit floating decimal points between 0 and 1.
*2 Combinatorial optimization problem: A problem seeking to determine the value (combination) of variables that optimizes a certain indicator (value) from among many different options under various constraints.
*3 Reinsurance portfolio optimization task: The task of designing a balanced risk portfolio that disperses multiple risks held by an insurance company by means of reinsurance contracts.
