Theoretical convergence of large-step primal-dual interior point algorithms for linear programming.
Masakazu KojimaNimrod MegiddoShinji MizunoPublished in: Math. Program. (1993)
Keyphrases
- linear programming
- stochastic approximation
- graph theory
- theoretical analysis
- orders of magnitude
- computational complexity
- complexity analysis
- worst case
- optimization problems
- data mining algorithms
- learning algorithm
- interior point
- iterative algorithms
- constraint propagation
- recently developed
- combinatorial optimization
- times faster
- computational efficiency
- significant improvement
- benchmark datasets
- convergence rate
- query language
- computational cost
- dynamic programming
- stopping criterion
- reinforcement learning
- data sets
- stopping criteria
- stochastic shortest path