Kantorovich Dual Problem (for general costs): Difference between revisions
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Type of this problem is stated by Caffarelli. We will provide the modern one. | Type of this problem is stated by Caffarelli. We will provide the modern one. | ||
During the pandemic, people are in the lockdown and it is the best time to enjoy a coffee time. All in all, it costs Amazon <math> c(x,y) </math> dollars to ship one box of necessary espresso capsules from place <math> x </math> to place <math> y </math>, i.e. from warehouses to homes. We want to optimize this expensive habit and consequently to solve appropriate Monge-Kantorovich problem. The mathematicians come to Amazon and propose the new kind of payment. For every box at place <math> x </math> they will charge <math> \varphi(x) </math> dollars and <math> \psi(y) </math> dollars to deliver at place <math> y </math>. However, mathematicians will not reveal their shipping routes. Of course, in order for Amazon to accept this offer, the price <math> \varphi(x)+\psi(y) \leq c(x,y).</math> The moral is that if the mathematicians are smart enough, they will be capable to make this shipment cheaper. This is provided by Kantorovich duality theorem. | During the pandemic, people are in the lockdown and it is the best time to enjoy a coffee time. All in all, it costs Amazon <math> c(x,y) </math> dollars to ship one box of necessary espresso capsules from place <math> x </math> to place <math> y </math>, i.e. from warehouses to homes. We want to optimize this expensive habit and consequently to solve appropriate Monge-Kantorovich problem. The mathematicians come to Amazon and propose the new kind of payment. For every box at place <math> x </math> they will charge <math> \varphi(x) </math> dollars and <math> \psi(y) </math> dollars to deliver at place <math> y </math>. However, mathematicians will not reveal their shipping routes. Of course, in order for Amazon to accept this offer, the price <math> \varphi(x)+\psi(y) \leq c(x,y).</math> The moral is that if the mathematicians are smart enough, they will be capable to make this shipment cheaper. This is provided by Kantorovich duality theorem. Take care that in the same cases, mathematicians will also give negative prices! | ||
==Statement of Theorem== | ==Statement of Theorem== |
Revision as of 01:56, 23 May 2020
Introduction
The main advantage of Kantorovich Problem, in comparison to Monge problem, is in the convex constraint property. It is possible to formulate the dual problem.
The Shipper's Problem
Type of this problem is stated by Caffarelli. We will provide the modern one.
During the pandemic, people are in the lockdown and it is the best time to enjoy a coffee time. All in all, it costs Amazon dollars to ship one box of necessary espresso capsules from place to place , i.e. from warehouses to homes. We want to optimize this expensive habit and consequently to solve appropriate Monge-Kantorovich problem. The mathematicians come to Amazon and propose the new kind of payment. For every box at place they will charge dollars and dollars to deliver at place . However, mathematicians will not reveal their shipping routes. Of course, in order for Amazon to accept this offer, the price The moral is that if the mathematicians are smart enough, they will be capable to make this shipment cheaper. This is provided by Kantorovich duality theorem. Take care that in the same cases, mathematicians will also give negative prices!
Statement of Theorem
- Theorem.[1] Let X and Y be Polish spaces, let and , and let a cost function be lower semi-continuous.
Whenever and , define
.
Define to be the set of Borel probability measures on such that for all measurable sets and ,
, ,
and define to be the set of all measurable functions satisfying for almost everywhere in X and almost everywhere in Y.
Then .
Moreover, the infimum is attained. In addition it is possible to restrict and to be continuous and bounded.
Outline of the Proof
References
- ↑ Cite error: Invalid
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- ↑ C. Villani, Topics in Optimal Transportation, Chapter 1. (pages 17-21)
- ↑ https://link-springer-com.proxy.library.ucsb.edu:9443/book/10.1007/978-3-319-20828-2 F. Santambrogio, Optimal Transport for Applied Mathematicians, Chapter 1.] (pages 9-16)