View source for 18371270. SYSTEM AND METHOD FOR ACCELERATING BENDERS DECOMPOSITION VIA REINFORCEMENT LEARNING SURROGATE MODELS simplified abstract (JPMorgan Chase Bank, N.A.)

=SYSTEM AND METHOD FOR ACCELERATING BENDERS DECOMPOSITION VIA REINFORCEMENT LEARNING SURROGATE MODELS=


==Organization Name==

[[:Category:JPMorgan Chase Bank, N.A.|JPMorgan Chase Bank, N.A.]]


[[Category:JPMorgan Chase Bank, N.A.]]

==Inventor(s)==

[[:Category:Kyle Mana of Renton WA (US)|Kyle Mana of Renton WA (US)]][[Category:Kyle Mana of Renton WA (US)]]

[[:Category:Parisa Zehtabi of London (GB)|Parisa Zehtabi of London (GB)]][[Category:Parisa Zehtabi of London (GB)]]

[[:Category:Hoa Lun Stephen Mak of Glasgow (GB)|Hoa Lun Stephen Mak of Glasgow (GB)]][[Category:Hoa Lun Stephen Mak of Glasgow (GB)]]

[[:Category:Michael Cashmore of Stirlingshire (GB)|Michael Cashmore of Stirlingshire (GB)]][[Category:Michael Cashmore of Stirlingshire (GB)]]

[[:Category:Daniele Magazzeni of London (GB)|Daniele Magazzeni of London (GB)]][[Category:Daniele Magazzeni of London (GB)]]

[[:Category:Manuela Veloso of New York NY (US)|Manuela Veloso of New York NY (US)]][[Category:Manuela Veloso of New York NY (US)]]

[[:Category:Daniel A Kirsner of Oak Park IL (US)|Daniel A Kirsner of Oak Park IL (US)]][[Category:Daniel A Kirsner of Oak Park IL (US)]]

[[:Category:Ryan Eiben of Lewis Center OH (US)|Ryan Eiben of Lewis Center OH (US)]][[Category:Ryan Eiben of Lewis Center OH (US)]]

[[:Category:Donald Stephens of Hollis NY (US)|Donald Stephens of Hollis NY (US)]][[Category:Donald Stephens of Hollis NY (US)]]

[[:Category:Lei Carol Liang of Hamburg NJ (US)|Lei Carol Liang of Hamburg NJ (US)]][[Category:Lei Carol Liang of Hamburg NJ (US)]]

[[:Category:Fernando Acero of London (GB)|Fernando Acero of London (GB)]][[Category:Fernando Acero of London (GB)]]

==SYSTEM AND METHOD FOR ACCELERATING BENDERS DECOMPOSITION VIA REINFORCEMENT LEARNING SURROGATE MODELS - A simplified explanation of the abstract==


This abstract first appeared for US patent application 18371270 titled 'SYSTEM AND METHOD FOR ACCELERATING BENDERS DECOMPOSITION VIA REINFORCEMENT LEARNING SURROGATE MODELS

'''Simplified Explanation''': 

The patent application discusses methods and systems for accelerating decomposition through reinforcement learning. It involves using a processor to implement a decomposition algorithm for solving large linear programming problems with a block structure, inserting a reinforcement learning agent into the algorithm, and generating master problem decisions to replace NP-hard mixed-integer master problems.

* Reinforcement learning integrated into a decomposition algorithm
* Accelerating decomposition of large linear programming problems
* Replacement of NP-hard mixed-integer master problems with master problem decisions
* Use of a processor to implement the algorithm
* Special block structure in the linear programming problems

'''Potential Applications''':
The technology could be applied in various industries such as logistics, finance, and manufacturing where optimization of complex problems is required.

'''Problems Solved''':
The technology addresses the challenge of efficiently solving large linear programming problems with a special block structure by incorporating reinforcement learning.

'''Benefits''':
- Faster decomposition of complex linear programming problems
- Improved efficiency in decision-making processes
- Enhanced optimization capabilities in various industries

'''Commercial Applications''':
Optimizing supply chain management, financial portfolio management, and production planning processes using the accelerated decomposition technology.

'''Prior Art''':
Researchers can explore prior studies on reinforcement learning in optimization algorithms and decomposition methods to understand the evolution of this technology.

'''Frequently Updated Research''':
Stay updated on advancements in reinforcement learning algorithms and their applications in optimization to enhance the efficiency of decomposition processes.

'''Questions about Accelerating Decomposition via Reinforcement Learning''':
1. How does reinforcement learning improve the efficiency of solving large linear programming problems?
2. What are the key differences between traditional decomposition methods and the approach involving reinforcement learning?


==Original Abstract Submitted==

Various methods, apparatuses/systems, and media for accelerating decomposition via reinforcement learning are disclosed. A processor implements a decomposition algorithm that allows a solution of a comparatively larger linear programming problems that have a special block structure; inserts a reinforcement learning agent within a framework of the decomposition algorithm; and generates, in response to inserting the reinforcement learning agent, master problem decisions in place of an NP-hard (nondeterministic polynomial time-hard) mixed-integer master problem (MIMP).



[[Category:G06F17/11]]
[[Category:CPC_G06F17/11]]