Math 2.0

Calculus of variations and optimal control; optimization Problem

Optimal transport and the Monge problem

Builds on Probability measurePushforward measureBorel measureMonge–Ampère equationWasserstein metric

Problem

Let XX and YY be complete separable metric spaces. Let μ\mu be a Borel probability measure on XX and ν\nu a Borel probability measure on YY. Let c ⁣:X×Y→[0,∞]c \colon X \times Y \to [0, \infty] be a lower semicontinuous cost function.

  1. Monge problem: minimize ∫Xc(x,T(x)) dμ(x)\int_X c(x, T(x)) \, d\mu(x) over all Borel maps T ⁣:X→YT \colon X \to Y with T#μ=νT_\# \mu = \nu, where T#μT_\# \mu is the pushforward measure T#μ(B)=μ(T−1(B))T_\#\mu(B) = \mu(T^{-1}(B)).
  2. Kantorovich problem: minimize ∫X×Yc dπ\int_{X \times Y} c \, d\pi over all transport plans, the Borel probability measures π\pi on X×YX \times Y with marginals μ\mu and ν\nu.

Decide when minimizers exist, when they are unique, and when an optimal plan is given by a map.

Remarks

Monge posed the problem in 1781, in his memoir on cuttings and fillings, for the cost c(x,y)=∣x−y∣c(x, y) = \abs{x - y} in ℝ3\R^3. His aim was to move a pile of soil into a hole of the same volume with least total work. The Monge problem may have no admissible map at all: if μ\mu is a Dirac mass and ν\nu is not, no TT satisfies T#μ=νT_\#\mu = \nu. Kantorovich introduced the relaxed problem in 1942; under the hypotheses above it always has a minimizer, by weak compactness of the set of plans and lower semicontinuity of the cost. For X=Y=ℝnX = Y = \R^n, c(x,y)=∣x−y∣2c(x, y) = \abs{x - y}^2, μ\mu absolutely continuous and both measures with finite second moments, Brenier's theorem gives a unique optimal plan, induced by the map T=∇φT = \nabla \varphi for a convex function φ\varphi. Then φ\varphi solves a Monge–Ampère equation in a weak sense, and the optimal cost defines the squared Wasserstein distance W2(μ,ν)2W_2(\mu, \nu)^2. For Monge's original cost ∣x−y∣\abs{x - y} in ℝn\R^n with μ\mu absolutely continuous and both measures with finite first moments, optimal maps exist but are in general not unique. Evans and Gangbo proved existence under extra hypotheses in 1999, and later work removed them.

Reading path

To understand this page from the ground up, read these 9 pages in order. The foundations come first.

Show the path as a graph
Each page uses the pages above it. The colour of the bar on a box shows how strong the evidence is, and the box also gives it as text. The list has the same pages.
  • no evidence level
  1. Borel sigma-algebra concept
  2. Measure concept
  3. Monge–Ampère equation concept
  4. Probability measure concept
  5. Pushforward measure concept
  6. Topological space concept
  7. Wasserstein metric concept
  8. Borel measure definition
  9. Optimal transport and the Monge problem problem

Further reading

  1. Web https://en.wikipedia.org/wiki/Transportation_theory_(mathematics)
About this page
TagK8EBASR5VG
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MSC49Q22, 35J96, 60A10
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AboutProbability measure, Pushforward measure
UsesProbability measure, Pushforward measure, Borel measure, Monge–Ampère equation, Wasserstein metric
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Changed2 November 2026

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