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Probabilistic Analysis Of Algorithms

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  • Rinnooy Kan, A. H. G.

Abstract

An introductory and selective review is presented of results obtained through a probabilistic analysis of combinatorial algorithms. The emphasis is on asymptotic characteristics of optimal solution values, and on the relative and absolute error analysis for simple heuristics.

Suggested Citation

  • Rinnooy Kan, A. H. G., 1985. "Probabilistic Analysis Of Algorithms," Econometric Institute Archives 272328, Erasmus University Rotterdam.
    • Handle: RePEc:ags:eureia:272328
    DOI: 10.22004/ag.econ.272328
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    References listed on IDEAS

    as
    1. Frieze, A. M. & Clarke, M. R. B., 1984. "Approximation algorithms for the m-dimensional 0-1 knapsack problem: Worst-case and probabilistic analyses," European Journal of Operational Research, Elsevier, vol. 15(1), pages 100-109, January.
    2. David G. Dannenbring, 1977. "Procedures for Estimating Optimal Solution Values for Large Combinatorial Problems," Management Science, INFORMS, vol. 23(12), pages 1273-1283, August.
    3. Richard M. Karp, 1977. "Probabilistic Analysis of Partitioning Algorithms for the Traveling-Salesman Problem in the Plane," Mathematics of Operations Research, INFORMS, vol. 2(3), pages 209-224, August.
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    Cited by:

    1. Harkema, R., 1985. "Minimum Sample Size Requirements For Maximum Likelihood Estimation Of Some Demand Models," Econometric Institute Archives 272292, Erasmus University Rotterdam.
    2. Boender, C. G. E. & Rinnooy Kan, A. H. G., 1985. "Bayesian Stopping Rules For Multistart Global Optimization Methods," Econometric Institute Archives 272326, Erasmus University Rotterdam.
    3. Awi Federgruen & Joern Meissner, 2004. "Probabilistic Analysis of Multi-Item Capacitated Lot Sizing Problems," Working Papers MRG/0004, Department of Management Science, Lancaster University, revised Apr 2005.

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