Binary Variable Penalty Term Generation for PUBO Solvers
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Solution Overview
Problem
Designing penalty terms for combinatorial optimization problems is challenging, as they can increase the number of decision variables and computation resources required, and their range often exceeds that of the original objective function, complicating calculations and potentially affecting precision.
Innovation Solution
An information processing device generates penalty terms with binary variable parameters by converting logical expression data from constraint data, using a generator and converter to create a penalty term that can be added to the objective function, allowing for efficient calculation of combinatorial optimization problems using a PUBO solver.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If penalty terms are designed by conventional methods, then constraints can be embedded into objective functions, but the number of decision variables increases and computation resources become too large
Solution Approach 1:
The patent changes the parameter representation of penalty terms from conventional continuous coefficients to binary variable parameters. This transformation allows the penalty term to be expressed in a form that can be directly processed by the PUBO solver, reducing the need for additional decision variables while maintaining constraint satisfaction capability.
Solution Approach 2:
The patent replaces the conventional penalty term design mechanism with a binary variable-based penalty term generation mechanism. Instead of using traditional continuous optimization approaches for penalty term design, the system uses binary variables and PUBO solver technology to automatically generate penalty terms, thereby reducing computational complexity and decision variable count.
2Reliability
If penalty terms are designed by conventional methods, then constraints can be embedded into objective functions, but the range of penalty terms becomes greater than the original objective function, making calculation difficult
Solution Approach 1:
The patent transforms the penalty term parameters into binary variables, which changes the parameter space and allows for more efficient calculation. The binary variable representation enables the PUBO solver to handle penalty terms more effectively, reducing the calculation difficulty while maintaining the ability to satisfy constraints.
Solution Approach 2:
The patent introduces binary variables as an intermediary between the constraint conditions and the objective function. These binary variables serve as a mediator that translates constraint requirements into a form that is computationally easier to handle, reducing the difficulty of detecting and measuring the optimal solution.
3Reliability
If penalty terms are designed by conventional methods, then constraints can be embedded into objective functions, but specialized knowledge is required and design becomes difficult
Solution Approach 1:
The patent enables the system to automatically generate penalty terms using binary variables and the PUBO solver, eliminating the need for manual design by specialists. The automated generation process serves itself by taking constraint conditions as input and producing ready-to-use penalty terms, making the process accessible without specialized knowledge.
Solution Approach 2:
The patent replaces the manual penalty term design process with an automated binary variable-based generation process. This substitution eliminates the need for specialized knowledge in penalty term design, as the system automatically generates appropriate penalty terms based on the constraint conditions provided.
Data Source
AI summary
According to one embodiment, an information processing device includes a first storage and a first processing circuit. The first storage is configured to store constraint data which includes a constraint of a combinatorial optimization problem expressed in a formal language. The first processing circuit is configured to generate logical expression data from the constraint data and generate a penalty term data including a penalty term having a binary variable parameter by converting the logical expression data.