Approximation Limitations of Pure Dynamic Programming

12/23/2020
by   Stasys Jukna, et al.
0

We prove the first, even super-polynomial, lower bounds on the size of tropical (min,+) and (max,+) circuits approximating given optimization problems. Many classical dynamic programming (DP) algorithms for optimization problems are pure in that they only use the basic min, max, + operations in their recursion equations. Tropical circuits constitute a rigorous mathematical model for this class of algorithms. An algorithmic consequence of our lower bounds for tropical circuits is that the approximation powers of pure DP algorithms and greedy algorithms are incomparable. That pure DP algorithms can hardly beat greedy in approximation, is long known. New in this consequence is that also the converse holds.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
03/14/2018

Greedy can also beat pure dynamic programming

Many dynamic programming algorithms are "pure" in that they only use min...
research
12/23/2020

Coin Flipping in Dynamic Programming is Almost Useless

We consider probabilistic circuits working over the real numbers, and us...
research
12/08/2021

A PTAS for the Min-Max Euclidean Multiple TSP

We present a polynomial-time approximation scheme (PTAS) for the min-max...
research
03/14/2018

Greedy can beat pure dynamic programming

Many dynamic programming algorithms for discrete 0-1 optimizationproblem...
research
06/05/2018

Dynamic Programming Optimization in Line of Sight Networks

Line of Sight (LoS) networks were designed to model wireless communicati...
research
07/05/2021

Polymorphic dynamic programming by algebraic shortcut fusion

Dynamic programming (DP) is a broadly applicable algorithmic design para...
research
01/20/2020

OpenMP Parallelization of Dynamic Programming and Greedy Algorithms

Multicore has emerged as a typical architecture model since its advent a...

Please sign up or login with your details

Forgot password? Click here to reset