Universal alignment probability revisited

Authors:
S. Y. Lin;Y. C. Ho
Affiliations:
Professor, Department of Electrical and Control Engineering, National Chiao Tung University, Hsinchu, Taiwan, ROC;Research Professor, Division of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts
Venue:
Journal of Optimization Theory and Applications
Year:
2002

Citing 1
Cited 6

Universal alignment probabilities and subset selection for ordinal optimization

Journal of Optimization Theory and Applications

Constrained Ordinal Optimization--A Feasibility Model Based Approach

Discrete Event Dynamic Systems
An ordinal optimization theory-based algorithm for a class of simulation optimization problems and application

Expert Systems with Applications: An International Journal
An ordinal optimization theory-based algorithm for large distributed power systems

Computers & Mathematics with Applications
Quantifying Heuristics in the Ordinal Optimization Framework

Discrete Event Dynamic Systems
Comparison of selection rules for ordinal optimization

Mathematical and Computer Modelling: An International Journal
Evolutionary algorithm assisted by surrogate model in the framework of ordinal optimization and optimal computing budget allocation

Information Sciences: an International Journal

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this note, we quantify and validate the representativeness of the uniformly sampled set N for the search space Θ and the use of universal alignment probability (UAP) curves.