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Solving Combinatorial Optimization Problems on Fujitsu Digital Annealer by Kao, Yu-Ting; Liao, Jia-Le; Hsu, Hsiu-Chuan is a scholarly article available to read on EtoBox.

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Combinatorial optimization problems are ubiquitous in various disciplines and applications. Many heuristic algorithms have been devoted to solve these types of problems. In order to increase the efficiency for finding the optimal solutions, an application-specific hardware, called digital annealer (DA) has been developed for solving combinatorial optimization problems using quadratic unconstrained binary optimization (QUBO) formulations. In this study, we formulated the number partitioning problem and the graph partitioning problem into QUBO forms and solved such problems with the DA developed by Fujitsu Ltd. The QUBO formulation of the number partitioning problem is fully connected. The DA found the overall runtime for the optimal solution to be less than 30 seconds for 6500 binary variables. For the graph partitioning problem, we adopted modularity as the metric for determining the quality of the partitions. For Zachary's Karate Club graph, the modularity obtained was 0.445, a 6% increase against D-wave Quantum Annealer and Simulated Annealing. Moreover, to explore the DA's potential applications to real-world problems, we used the search for communities or virtual microgrids in

Author

Kao, Yu-Ting; Liao, Jia-Le; Hsu, Hsiu-Chuan

Published

2023

Language

EN