Information Processing Circuit for Rapid Combination Optimization
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Solution Overview
Problem
Existing systems face challenges in generating combination optimization problems at high speed, particularly in dynamic situations where rapid changes require frequent problem generation and solution processing.
Innovation Solution
An information processing device that includes a solver device and an information processing circuit, where the circuit generates combination optimization problems by creating weight values based on input data and stores them in a memory, allowing the solver device to read and solve the problems efficiently.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If the combination optimization problem is generated and solved frequently to respond to changing situations, then the responsiveness is improved, but the time required for problem generation and processing increases
Solution Approach 1:
The patent pre-generates multiple combination optimization problems in advance and stores them in a storage unit before they are actually needed. When a situation change occurs, the system can immediately retrieve a pre-generated problem from storage without undergoing the full generation process, thereby reducing processing time while maintaining responsiveness.
2Adaptability or versatility
If the number of decision variables in the combination optimization problem increases to handle complex situations, then the problem-solving capability is improved, but the calculation difficulty increases exponentially
Solution Approach 1:
The system pre-generates and stores multiple combination optimization problems with varying numbers of decision variables and structures. When a complex situation arises, the system can retrieve a pre-generated problem that is specifically tailored to handle complex scenarios, avoiding the need to perform computationally intensive real-time generation of large-scale optimization problems.
Solution Approach 2:
The patent varies parameters such as the number of decision variables, the structure of the cost function, and the constraints in pre-generated optimization problems. This allows the system to select from a diverse set of pre-generated problems with different computational complexities, matching the problem parameters to the specific situation at hand without always requiring maximum complexity.
Data Source
AI summary
An information processing device according to an embodiment executes processing on data. The information processing device includes a solver device and an information processing circuit. The circuit acquires data and generates a combination optimization problem based on the data. The circuit causes the solver device to solve the combination optimization problem. A first partial weight group being part of weight values is the same as a second partial weight group being other part of the weight values. The circuit writes the first partial weight group and the second partial weight group in a common region in a first memory, and gives, to the solver device, first information indicating a storage position of each of the weight values in the first memory. The solver device reads weight values from the first memory on the basis of the first information and obtains the solution.