We show that it is not possible to speed-up the Knapsack problem efficiently in the parallel algebraic decision tree model. More specifically, we prove that any parallel algorithm in the fixed degree algebraic decision tree model that solves the decision version of the Knapsack problem requires Omega(sqrt(n)) rounds even by using 2^sqrt(n) processors. We extend the result to the PRAM model without bit-operations. These results are consistent with Mulmuley's recent result on the separation of the strongly-polynomial class and the corresponding NC class in the arithmetic PRAM model.Keywords lower-bounds, parallel algorithms, algebraic decision tre
AbstractAlready 30 years ago, Chvátal has shown that some instances of the zero-one knapsack problem...
There are a number of fundamental problems in computational geometry for which work-optimal algorith...
We analyze the computational complexity of three fundamental variants of the bilevel knapsack proble...
AbstractWe present lower bounds on the number of rounds required to solve a decision problem in the ...
We define a natural and realistic model of parallel computation called the PRAM model without bit op...
AbstractComputing an optimal solution to the knapsack problem is known to be NP-hard. Consequently, ...
We show various hardness results for knapsack and related problems; in particular we will show that ...
hard problem but does admit a pseudo-polynomial time algorithm and can be solved efficiently if the ...
We consider parallel random access machines (PRAM's) with p processors and distributed systems of ra...
We show various hardness of approximation algorithms for knapsack and related problems; in particula...
AbstractIn this paper, we study the algebraic complexity of the knapsack problem in the form a⊤x = 1...
This paper presents a new semantic method for proving lower bounds in computational complexity. We u...
We prove Ω(n²) complexity lower bound for the general model of randomized computation trees solving ...
We prove Ω(n²) complexity lower bound for the general model of randomized computation trees solving ...
We show that proving lower bounds in algebraic models of computation may not be easier than in the s...
AbstractAlready 30 years ago, Chvátal has shown that some instances of the zero-one knapsack problem...
There are a number of fundamental problems in computational geometry for which work-optimal algorith...
We analyze the computational complexity of three fundamental variants of the bilevel knapsack proble...
AbstractWe present lower bounds on the number of rounds required to solve a decision problem in the ...
We define a natural and realistic model of parallel computation called the PRAM model without bit op...
AbstractComputing an optimal solution to the knapsack problem is known to be NP-hard. Consequently, ...
We show various hardness results for knapsack and related problems; in particular we will show that ...
hard problem but does admit a pseudo-polynomial time algorithm and can be solved efficiently if the ...
We consider parallel random access machines (PRAM's) with p processors and distributed systems of ra...
We show various hardness of approximation algorithms for knapsack and related problems; in particula...
AbstractIn this paper, we study the algebraic complexity of the knapsack problem in the form a⊤x = 1...
This paper presents a new semantic method for proving lower bounds in computational complexity. We u...
We prove Ω(n²) complexity lower bound for the general model of randomized computation trees solving ...
We prove Ω(n²) complexity lower bound for the general model of randomized computation trees solving ...
We show that proving lower bounds in algebraic models of computation may not be easier than in the s...
AbstractAlready 30 years ago, Chvátal has shown that some instances of the zero-one knapsack problem...
There are a number of fundamental problems in computational geometry for which work-optimal algorith...
We analyze the computational complexity of three fundamental variants of the bilevel knapsack proble...