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Ordinal Hill Climbing Algorithms for Discrete Manufacturing Process Design Optimization Problems
Authors:Kelly A Sullivan  Sheldon H Jacobson
Affiliation:(1) United Airlines, Chicago, Illinois;(2) Department of Mechanical and Industrial Engineering, University of Illinois at Urbana-Champaign, Urbana, Illinois USA, 61801
Abstract:Thispaper introduces ordinal hill climbing algorithms for addressingdiscrete manufacturing process design optimization problems usingcomputer simulation models. Ordinal hill climbing algorithmscombine the search space reduction feature of ordinal optimizationwith the global search feature of generalized hill climbing algorithms.By iteratively applying the ordinal optimization strategy withinthe generalized hill climbing algorithm framework, the resultinghybrid algorithm can be applied to intractable discrete optimizationproblems. Computational results on an integrated blade rotormanufacturing process design problem are presented to illustratethe application of the ordinal hill climbing algorithm. The relationshipbetween ordinal hill climbing algorithms and genetic algorithmsis also discussed. This discussion provides a framework for howthe ordinal hill climbing algorithm fits into currently appliedalgorithms, as well as to introduce a bridge between the twoalgorithms.
Keywords:stochastic algorithms  ordinal optimization  optimization  hill climbing  genetic algorithms  manufacturing process design
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