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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. 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.
    3. David G. Dannenbring, 1977. "Procedures for Estimating Optimal Solution Values for Large Combinatorial Problems," Management Science, INFORMS, vol. 23(12), pages 1273-1283, August.
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    Cited by:

    1. 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.
    2. Harkema, R., 1985. "Minimum Sample Size Requirements For Maximum Likelihood Estimation Of Some Demand Models," Econometric Institute Archives 272292, 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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