Mentioned before we connected with D-Wave Quantum Computing early on. Have posted many items about their work. Their annealing approach still has great potential for some difficult kinds of combinatorial problems. Note how this addresses partitioning of sub problems to make the D-Wave approach most useful. Here a new example of work from Japan in the automotive manufacturing space. Not enough detail here, but taking a closer look.
Algorithm Optimizes Quantum Computing Problem-Solving
Tohoku University in ACM
Researchers at Tohoku University in Japan have developed an algorithm that augments the ability of a Canadian-designed quantum computer to more efficiently determine an optimized solution for complex problems. The D-Wave quantum annealer uses the concepts of quantum physics to solve "combinatorial optimization problems;” Tohoku's Shuntaro Okada and Masayuki Ohzeki designed the algorithm with global automotive components manufacturer Denso and other collaborators, to improve this capability. The algorithm partitions a large problem into a group of subproblems, then the annealer iteratively optimizes each subproblem to solve the overarching one. The program also enhances another algorithm via the same concept, permitting the use of larger subproblems, and more efficiently arriving at optimal solutions. Ohzeki said, "As the number of [quantum bits] mounted in the D-Wave quantum annealer increases, we will be able to obtain even better solutions." ... '
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