An explanation of ordinal optimization: Soft computing for hard problems

DOI10.1016/S0020-0255(98)10056-7zbMath0931.90072WikidataQ126322766 ScholiaQ126322766MaRDI QIDQ1818951

Yu-Chi Ho

Publication date: 5 January 2000

Published in: Information Sciences (Search for Journal in Brave)

zbMATH Keywords

ordinal optimizationsoft computingtutorialsystem performance evaluation

Mathematics Subject Classification ID

Applications of mathematical programming (90C90) Special problems of linear programming (transportation, multi-index, data envelopment analysis, etc.) (90C08)

Related Items (15)

Constrained ordinal optimization -- a feasibility model based approach ⋮ Demonstration of probabilistic ordinal optimization concepts for continuous-variable optimization under uncertainty ⋮ Quantifying heuristics in the ordinal optimization framework ⋮ Simple explanation of the no-free-lunch theorem and its implications ⋮ Multi-objective ordinal optimization for simulation optimization problems ⋮ Comparison of selection rules for ordinal optimization ⋮ Embedding evolutionary strategy in ordinal optimization for hard optimization problems ⋮ The equivalence between ordinal optimization in deterministic complex problems and in stochastic simulation problems ⋮ A new approach to discrete stochastic optimization problems ⋮ Ordinal optimization and quantification of heuristic designs ⋮ Simulation optimization: a review of algorithms and applications ⋮ Constraint ordinal optimization ⋮ Ordinal optimization of \(G/G/1/K\) polling systems with \(k\)-limited service discipline ⋮ An ordinal optimization based evolution strategy to schedule complex make-to-order products ⋮ A probabilistic solution-generator for simulation

Cites Work

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• Ordinal optimization of DEDS
• Universal alignment probabilities and subset selection for ordinal optimization
• Convergence properties of ordinal comparison in the simulation of discrete event dynamic systems
• Rates of convergence of ordinal comparison for dependent discrete event dynamic systems
• Dynamics and convergence rate of ordinal comparison of stochastic discrete-event systems
• Explanation of goal softening in ordinal optimization
• Motion planning of walking robots in environments with uncertainty

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