Kabushiki kaisha toshiba (20240095300). SOLUTION FINDING DEVICE, SOLUTION FINDING METHOD, AND COMPUTER PROGRAM PRODUCT simplified abstract
Contents
- 1 SOLUTION FINDING DEVICE, SOLUTION FINDING METHOD, AND COMPUTER PROGRAM PRODUCT
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 SOLUTION FINDING DEVICE, SOLUTION FINDING METHOD, AND COMPUTER PROGRAM PRODUCT - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Potential Applications
- 1.6 Problems Solved
- 1.7 Benefits
- 1.8 Potential Commercial Applications
- 1.9 Possible Prior Art
- 1.10 Original Abstract Submitted
SOLUTION FINDING DEVICE, SOLUTION FINDING METHOD, AND COMPUTER PROGRAM PRODUCT
Organization Name
Inventor(s)
Masaru Suzuki of Ota Tokyo (JP)
SOLUTION FINDING DEVICE, SOLUTION FINDING METHOD, AND COMPUTER PROGRAM PRODUCT - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240095300 titled 'SOLUTION FINDING DEVICE, SOLUTION FINDING METHOD, AND COMPUTER PROGRAM PRODUCT
Simplified Explanation
The patent application describes a solution-finding device for solving a 0-1 combinatorial optimization problem with constraint conditions expressed using inequality expressions. The device includes an updating unit and an output unit.
- The updating unit sequentially updates the first and second variables associated with plural elements for each unit-time between initial timing and end timing.
- The output unit outputs the solution of the optimization problem based on the first variable of each element at the end timing.
- During the updating operation, if the inequality expression with the first variable substituted is unsatisfied for one or more constraint conditions, the updating unit subtracts a correction value from the second variable of each element based on the distance from the boundary of the inequality expression to positions identified by the elements.
Potential Applications
This technology can be applied in various fields such as logistics, scheduling, resource allocation, and network optimization.
Problems Solved
1. Efficiently solving 0-1 combinatorial optimization problems with constraint conditions. 2. Handling multiple constraint conditions simultaneously during the solution-finding process.
Benefits
1. Improved optimization of resources and decision-making processes. 2. Increased efficiency in finding solutions to complex combinatorial problems.
Potential Commercial Applications
1. Supply chain management software. 2. Project management tools for scheduling and resource allocation.
Possible Prior Art
One possible prior art could be similar solution-finding devices used in mathematical optimization algorithms.
Unanswered Questions
How does this technology compare to existing optimization algorithms in terms of efficiency and accuracy?
This article does not provide a direct comparison with existing optimization algorithms. Further research and testing would be needed to determine the performance of this technology in comparison to others.
What are the potential limitations or drawbacks of this solution-finding device in practical applications?
The article does not address any potential limitations or drawbacks of the device. Additional studies and real-world implementations would be necessary to identify any challenges or constraints in using this technology.
Original Abstract Submitted
a 0-1 combinatorial-optimization-problem is solved under constraint-conditions expressed using inequality expressions. a solution-finding device includes an updating-unit and an output-unit. for each of plural elements associated with first- and second-variables, the updating-unit sequentially updates, for each unit-time between initial-timing and end-timing, the first-variable and the second-variable alternatively. the output-unit outputs the solution of the 0-1 combinatorial-optimization-problem based on the first-variable of each of the plural elements at the end-timing. during the updating operation for each unit-time, for each of one or more constraint-conditions, when the inequality expression in which the first-variable corresponding to each of the plural discrete variables is substituted is unsatisfied; the updating-unit subtracts, from the second-variable of each of the plural elements, a correction value corresponding to the component of the element corresponding to the distance from the boundary of the inequality expression to positions identified by the plural elements.
