Ising Machine Penalty Coefficient Setting for Logical Constraints
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Solution Overview
Problem
Existing methods for setting penalty coefficients in Ising machines when dealing with logical operations in combinatorial optimization problems are inefficient, especially when the initial value of the penalty coefficient deviates significantly from the appropriate value.
Innovation Solution
An information processing apparatus and method that utilize a penalty coefficient setting unit to determine an appropriate penalty coefficient based on the constraint condition related to logical operations. This is achieved by calculating the weight of the penalty function using the energy function and the model coefficient, ensuring the solution satisfies the logical constraint.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the penalty coefficient is set too small, then the solution does not satisfy the constraint condition, but if the penalty coefficient is set too large, then the influence of the original evaluation index on the solution becomes small
Solution Approach 1:
The patent transforms the logical constraint satisfaction problem into a parameter optimization problem by introducing a penalty coefficient that can be adjusted. By changing the parameter (penalty coefficient) dynamically, the system achieves both constraint satisfaction and preservation of evaluation index accuracy. The penalty coefficient serves as a controllable parameter that balances between enforcing constraints and maintaining the original optimization objective.
Solution Approach 2:
The patent employs a dynamic approach where the penalty coefficient is not fixed but can be adjusted during the optimization process. This dynamic adjustment allows the system to adaptively balance constraint satisfaction and evaluation index accuracy, resolving the contradiction between these two requirements through iterative optimization.
2Ease of operation
If existing methods are used to set penalty coefficients, then the process is simple, but the setting is inefficient when the initial value deviates significantly from the appropriate value
Solution Approach 1:
The patent implements a feedback mechanism where the penalty coefficient is adjusted based on the observed performance of the optimization process. By monitoring whether constraints are satisfied and whether the evaluation index accuracy is maintained, the system provides feedback to adjust the penalty coefficient, thereby improving efficiency without sacrificing ease of operation.
Solution Approach 2:
The patent performs preliminary analysis of the logical constraints to determine appropriate initial values or ranges for the penalty coefficient. This preliminary action ensures that even when the initial value deviates from the optimal, the system can efficiently converge to the correct solution by having a better starting point based on prior analysis of the constraint structure.
Data Source
AI summary
According to a preferred aspect of the invention, provided is an information processing apparatus including a processor and a storage device. A penalty coefficient setting unit is implemented by the processor and the storage device using a solution finding function for obtaining a solution of a combinatorial optimization problem using a cost function and a constraint condition. The penalty coefficient setting unit sets a penalty function and a penalty coefficient based on the constraint condition related to a logical operation imposed between two variables of the cost function and a value of a model coefficient of the cost function such that the solution of the combinatorial optimization problem satisfies the constraint condition, and searches for the solution of the combinatorial optimization problem based on the penalty function and the penalty coefficient.