On optimality of a polynomial algorithm for random linear multidimensional assignment problem

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

We demonstrate that the linear multidimensional assignment problem with iid random costs is polynomially e{open}-approximable almost surely (a. s.) via a simple greedy heuristic, for a broad range of probability distributions of the assignment costs. Specifically, conditions on discrete and continuous distributions of the cost coefficients, including distributions with unbounded support, have been established that guarantee convergence to unity in the a. s. sense of the cost ratio between the greedy solution and optimal solution. The corresponding convergence rates have been determined.

Original languageEnglish (US)
Pages (from-to)153-164
Number of pages12
JournalOptimization Letters
Volume5
Issue number1
DOIs
StatePublished - Jan 1 2011
Externally publishedYes

Fingerprint

Polynomial Algorithm
Assignment Problem
Optimality
Costs
Greedy Heuristics
Discrete Distributions
Continuous Distributions
Convergence Rate
Assignment
Probability Distribution
Optimal Solution
Coefficient
Range of data
Demonstrate

Keywords

  • Approximability
  • Convergence almost surely
  • Greedy heuristic
  • Multidimensional assignment problem

ASJC Scopus subject areas

  • Control and Optimization

Cite this

On optimality of a polynomial algorithm for random linear multidimensional assignment problem. / Krokhmal, Pavlo A.

In: Optimization Letters, Vol. 5, No. 1, 01.01.2011, p. 153-164.

Research output: Contribution to journalArticle

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