Efficient on-line algorithms for the knapsack problem
14th International Colloquium on Automata, languages and programming
Probabilistic analysis of the multidimensional knapsack problem
Mathematics of Operations Research
A probabilistic analysis of the multiknapsack value function
Mathematical Programming: Series A and B
On rates of convergence and Asymptotic normality in the multiknapsack problem
Mathematical Programming: Series A and B
Average-case analysis of off-line and on-line knapsack problems
Journal of Algorithms - Special issue on SODA '95 papers
Approximate Algorithms for the 0/1 Knapsack Problem
Journal of the ACM (JACM)
Fast Approximation Algorithms for the Knapsack and Sum of Subset Problems
Journal of the ACM (JACM)
On finding the exact solution of a zero-one knapsack problem
STOC '84 Proceedings of the sixteenth annual ACM symposium on Theory of computing
Video quality and system resources: Scheduling two opponents
Journal of Visual Communication and Image Representation
A rough set based approach to patent development with the consideration of resource allocation
Expert Systems with Applications: An International Journal
Greedy algorithms for the minimization knapsack problem: Average behavior
Journal of Computer and Systems Sciences International
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We consider the average-case performance of a well-known approximation algorithm for the 0/1 knapsack problem, the decreasing density greedy (DDG) algorithm. Let U"n={u"1,...,u"n} be a set of n items, with each item u"i having a size s"i and a profit p"i, and K"n be the capacity of the knapsack. Given an instance of the 0/1 knapsack problem, let P"L denote the total profit of an optimal solution of the linear version of the problem (i.e., a fraction of an item can be packed in the knapsack) and P"D"D"G denote the total profit of the solution obtained by the DDG algorithm. Assuming that U"n is a random sample from the uniform distribution over (0,1]^2 and K"n=@sn for some constant 0