Constraint ordinal optimization

Authors:
David Li;Loo Hay Lee;Yu Chi Ho
Affiliations:
140 Cottonwood Ct., Mountain View, CA;Department of Industrial and Systems Engineering, National University of Singapore, Kent Ridge, Singapore 119260;Division of Engineering and Applied Sciences, Harvard University, Cambridge, MA
Venue:
Information Sciences—Applications: An International Journal
Year:
2002

Citing 6
Cited 2

Adaptation in natural and artificial systems

Adaptation in natural and artificial systems
Convergence properties of ordinal comparison in the simulation of discrete event dynamic systems

Journal of Optimization Theory and Applications
Universal alignment probabilities and subset selection for ordinal optimization

Journal of Optimization Theory and Applications
An explanation of ordinal optimization: soft computing for hard problems

Information Sciences: an International Journal
Multi-product planning and scheduling using genetic algorithm approach

Computers and Industrial Engineering
Introduction to Stochastic Dynamic Programming: Probability and Mathematical

Introduction to Stochastic Dynamic Programming: Probability and Mathematical

Constrained Ordinal Optimization--A Feasibility Model Based Approach

Discrete Event Dynamic Systems
Multi-objective ordinal optimization for simulation optimization problems

Automatica (Journal of IFAC)

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Abstract

Ordinal optimization has been developed as the solution to single performance measurement problem. However, in reality, multiple performance measures are required to solve optimization problems. Constraint optimization was developed so that single measure could be optimized while the remaining performance measures were used as constraints. In this paper, we will build a new framework and quantification methods for dealing with the constraint optimization problem. We call the framework constraint ordinal optimization.