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Analysis · Concept hub

Linear Programming

1939 CEIndependent 20th-century routes through Soviet production planning and American military and administrative planning

Through Linear Programming: How can we recognize the same structure inside different problems?

Use rotations, permutations, matrices, and categories to read transformation rules and relationships rather than appearances.

This voyage is an editorial path for understanding, not a claim of direct historical influence or sole invention.

Understand it in one breath

Optimize a linear objective over a region cut out by linear constraints. If a finite optimum exists and the feasible region has vertices, at least one optimal vertex exists. An entire edge can also be optimal, and a model may be infeasible or unbounded. Simplex and interior-point methods support resource allocation, flow, and production planning.

At a glance

Scenario

Constraints

Objective

Optimum

Factory resource allocation

Materials ≤ 100; labor ≤ 80

Profit = 5x + 3y → max

One of the vertices

Blending and mixing

Ingredients, nutrition, and demand

Cost → min

An LP when quantities are continuous

Network flow

Capacity and flow conservation

Cost → min

Some routing and transport problems

Linear approximation to power dispatch

Demand and capacity

Operating cost → min

Real systems add nonlinear and integer constraints

Some linear-classification variants

Linear constraints

Linear loss or cost → min

Can be an LP; a standard SVM is usually a quadratic program

The simplex algorithm moves among adjacent basic feasible solutions, while interior-point methods travel through the feasible region. Model quality also depends on how faithfully the objective and constraints represent reality.

Concept

Optimize a linear objective over a feasible region defined by linear constraints. Kantorovich’s 1939 production planning and Dantzig’s 1947 planning model and simplex method formed in different institutions; a model may be infeasible, unbounded, or have multiple optima.

Key formula

max  cxs.t. Axb,  x0\max\; \mathbf{c}^\top \mathbf{x} \quad \text{s.t. } A\mathbf{x} \leq \mathbf{b},\; \mathbf{x} \geq 0

Ports in time

This concept was not invented in one instant

Follow the scenes to see problems, notation, standards of proof, and applications changing across different times and places.

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Kantorovich — production planning with scarce resources

In Leningrad, linear inequalities and solution methods were applied to production allocation. The work remained little known in the West for years and is not treated as a direct transmission into the later American route.

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Dantzig — the planning model and simplex method

In US Air Force planning, Dantzig developed a method that improves an objective by moving among vertices of a feasible polytope. Programming meant organizing plans more than writing code.

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Khachiyan — the first polynomial-time LP algorithm

The ellipsoid method showed that linear programming is solvable in polynomial time in theory. Worst-case complexity and practical speed are different comparisons.

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Karmarkar — a polynomial-time route through the interior

Karmarkar opened a major era for interior-point methods, but his was not the first polynomial-time LP algorithm and it did not replace simplex in every setting.

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Modern applications

Airline and logistics planning, network routing, portfolio optimization, and support-vector machines.

Beyond MathVoyage

Curated sources and problems. Bring one discovery back from OEIS, Project Euler, MathOverflow, or arXiv.

No concept belongs to one person

Follow people who played different roles

These are not inventor credits. They are different ports: opening a problem, sharpening a language, or carrying it into another world.

Number lenses

A concept looks different when its world of numbers changes

These numbers are editorial lenses for the voyage, not required prerequisites.

Concept genealogy

What supports it, and what does it open?

Concepts arriving from before

Current port

Linear Programming

Concepts opened from here

No direct successor port is curated yet.

Only direct editorial links are shown; this is not a complete learning order or historical influence line.