Ordinal hill climbing algorithms for discrete manufacturing process design optimization problems

This paper introduces ordinal hill climbing algorithms for addressing discrete manufacturing process design optimization problems using computer simulation models. Ordinal hill climbing algorithms combine the search space reduction feature of ordinal optimization with the global search feature of generalized hill climbing algorithms. By iteratively applying the ordinal optimization strategy within the generalized hill climbing algorithm framework, the resulting hybrid algorithm can be applied to intractable discrete optimization problems. Computational results on an integrated blade rotor manufacturing process design problem are presented to illustrate the application of the ordinal hill climbing algorithm. The relationship between ordinal hill climbing algorithms and genetic algorithms is also discussed. This discussion provides a framework for how the ordinal hill climbing algorithm fits into currently applied algorithms, as well as to introduce a bridge between the two algorithms.