• Linear programming

A

• Affine scaling
• Assignment problem

B

• Basic feasible solution
• Basic solution (linear programming)
• Benders decomposition
• Benson's algorithm
• Big M method

C

• Cashflow matching
• Configuration linear program
• Criss-cross algorithm
• Cunningham's rule

D

• Dantzig–Wolfe decomposition
• Data envelopment analysis
• Drawdown (economics)
• Dual cone and polar cone
• Dual linear program
• Duality (optimization)
• Duality gap

E

• Ellipsoid method
• Expected shortfall

F

• Farkas' lemma
• Fundamental theorem of linear programming

G

• GLOP
• Graver basis
• Gurobi Optimizer

H

• HiGHS optimization solver
• Hilbert basis (linear programming)
• Hirsch conjecture

I

• Integer points in convex polyhedra

K

• Karmarkar's algorithm
• Klee–Minty cube

L

• Linear inequality
• Linear programming decoding
• Linear programming relaxation
• Linear-fractional programming
• LP-type problem

M

• Mehrotra predictor–corrector method
• Minimum relevant variables in linear system
• MPS (format)
• Multi-objective linear programming

N

• N-dimensional polyhedron
• Network simplex algorithm

O

• Omega ratio

P

• Perturbation function
• Prune and search

R

• Reduced cost
• Revised simplex method

S

• Semidefinite programming
• Set cover problem
• Simplex algorithm
• Slack variable
• Stigler diet
• Strong duality

T

• Theory of two-level planning
• Total dual integrality

V

• Vertex enumeration problem

W

• Weak duality

Z

• Zadeh's rule