New multi-policy-based annealer for solving real-world combinatorial optimization problems tokodai_news
has grown accustomed to an efficient delivery of goods right at our doorsteps. But did you know that realizing such an efficiency requires solving a mathematical problem, namely what is the best possible route between all the destinations? Known as the"traveling salesman problem," this belongs to a class of mathematical problems known as"combinatorial optimization" problems.
Yet, a numerical study done by Tokyo Tech researchers has shown that while there exists many annealing computation methods, there is no one method suitable for solving a broad class of CO problems. Therefore, there is a need for an annealing mechanism that features multiple annealing methods to target a variety of such problems.
"In the annealing computation, a CO problem is represented as an energy function in terms of spin vectors. We start from an initially randomized spin vector configuration and then update it stochastically to find the minimum energy states by reducing its temperature. This closely mirrors the annealing process of metals where hot metals are cooled down in a controlled manner," explains Dr. Kawamura.
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