View source for 18372413. DATA PROCESSING APPARATUS AND DATA PROCESSING METHOD simplified abstract (Fujitsu Limited)

=DATA PROCESSING APPARATUS AND DATA PROCESSING METHOD=


==Organization Name==

[[:Category:Fujitsu Limited|Fujitsu Limited]]


[[Category:Fujitsu Limited]]

==Inventor(s)==

[[:Category:Sigeng Chen of Toronto (CA)|Sigeng Chen of Toronto (CA)]][[Category:Sigeng Chen of Toronto (CA)]]

[[:Category:Jeffrey Seth Rosenthal of Toronto (CA)|Jeffrey Seth Rosenthal of Toronto (CA)]][[Category:Jeffrey Seth Rosenthal of Toronto (CA)]]

[[:Category:Ali Sheikholeslamii of Toronto (CA)|Ali Sheikholeslamii of Toronto (CA)]][[Category:Ali Sheikholeslamii of Toronto (CA)]]

[[:Category:Hirotaka Tamura of Yokohama (JP)|Hirotaka Tamura of Yokohama (JP)]][[Category:Hirotaka Tamura of Yokohama (JP)]]

[[:Category:Aki Dote of Kawasaki (JP)|Aki Dote of Kawasaki (JP)]][[Category:Aki Dote of Kawasaki (JP)]]

==DATA PROCESSING APPARATUS AND DATA PROCESSING METHOD - A simplified explanation of the abstract==


This abstract first appeared for US patent application 18372413 titled 'DATA PROCESSING APPARATUS AND DATA PROCESSING METHOD

==Simplified Explanation==

The storing unit in the patent application stores coefficients and values of a coefficient group associated with a selected variable group. The searching unit searches for a solution to an optimization problem by updating the evaluation function based on the coefficient group values. The processing unit calculates multiplicity to determine when to switch to a different variable group during the search process.

* The storing unit stores coefficients and values of a coefficient group.
* The searching unit updates the evaluation function using the coefficient group values.
* The processing unit calculates multiplicity to determine when to switch variable groups.

== Potential Applications ==
This technology could be applied in various optimization problems in fields such as finance, logistics, and engineering where efficient search algorithms are required.

== Problems Solved ==
This technology helps in finding optimal solutions to complex optimization problems by efficiently updating the evaluation function based on coefficient group values.

== Benefits ==
The benefits of this technology include improved search efficiency, faster convergence to optimal solutions, and adaptability to different variable groups.

== Potential Commercial Applications ==
One potential commercial application of this technology could be in the development of advanced optimization software for industries such as supply chain management, financial modeling, and data analysis.

== Possible Prior Art ==
One possible prior art for this technology could be related to Markov chain Monte Carlo (MCMC) methods in 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 to evaluate the efficiency and accuracy of the proposed technology.

=== What are the specific industries or sectors that could benefit the most from implementing this technology? ===
The article does not specify the industries or sectors that could benefit the most from implementing this technology.


==Original Abstract Submitted==

A storing unit stores, amongst coefficients, values of a coefficient group associated with one selected from multiple variable groups, which are obtained by dividing state variables of an evaluation function. A searching unit searches for a solution to an optimization problem by repeating update processing, which includes calculating, using the values of the coefficient group, a value change of the evaluation function responsive to changing the value of each state variable of the variable group and changing the value of one state variable thereof based on the value change and temperature. A processing unit calculates multiplicity indicating the iteration count in which the values of the variable group are maintained in a search using Markov chain Monte Carlo (MCMC), and causes, responsive to cumulated multiplicity exceeding a threshold, the searching unit to perform the update processing using the values of the coefficient group associated with a different variable group.



[[Category:G06F17/18]]