Application study of simulated annealing solver and CIM simulator based on QUBO model using kaiwu SDK

In this paper, a methodology for finding the optimal solution by building a QUBO (Quadratic Unconstrained Binary Optimisation) model and using a combination of the Simulated Annealing algorithm and the CIM (Coherent Equivalent Machine) simulator in the Open Matter SDK will be presented. Firstly, the QUBO model was chosen because of its significant advantages in dealing with logical inference and combinatorial optimisation problems. The QUBO model provides an efficient solution method by transforming the problem into a quadratic unconstrained binary optimisation problem. In solving this problem, the first step is to define the objective and constraints of the problem, where the objective is to satisfy the relevant requirements and make the best of them, and the constraints are the relevant parameters provided by the data, and to build a mathematical model that matches the QUBO model. Next, a simulated annealing algorithm and a CIM simulator were used to solve this QUBO problem. By combining the QUBO model with these two algorithms, the optimal solution can be searched efficiently. Finally, the optimal solution is derived from the solution results. These scenarios not only satisfy the constraints but also achieve the given objective by optimising the combination of decision variables.