Ordinal Hill Climbing Algorithms for Discrete Manufacturing Process Design Optimization Problems

• Chen, C. H., and Kumar, V. 1996. Motion planning of walking robots in environments with uncertainty. Proceedings of IEEE Conference on Robotics and Automation.

• Dai, L. 1996. Convergence properties of ordinal comparison in the simulation of discrete event dynamic systems. Journal of Optimization Theory and Application 91(2): 363-388.

  Google Scholar 

• Fischer, C. E., Gunasakera, J. S., and Malas, J. C. 1997. Process model development for optimization of forged disk manufacturing processes. Steel Forgings, Second Volume, ASTM STP 1257. E. G. Nisbett and A. S. Melilli, eds. American Society for Testing and Materials.

• Gunasakera, J. S., Fischer, C. E., Malas, J. C., Mullins, W. M., and Yang, M. S. 1996. Development of process models for use with global optimization of a manufacturing system. Proceedings of the ASME Symposium on Modeling, Simulation, and Control of Metal Processing, ASME-International Mechanical Engineering Congress, Atlanta, GA, November.

• Ho, Y. C., Sreenivas, R., and Vakili, P. 1992. Ordinal optimization of discrete event dynamic systems. Journal of Discrete Event Dynamical Systems 2(2): 61-88.

  Google Scholar 

• Jacobson, S. H., Sullivan, K. A., and Johnson, A. W. 1997. Generalized hill climbing algorithms for discrete manufacturing process design problems using computer simulation models. Proceedings of the 11th European Simulation Multiconference, Istanbul, Turkey, June 1-4, pp. 473-478.

• Jacobson, S. H., Sullivan, K. A., and Johnson, A. W. 1998. Discrete manufacturing process design optimization using computer simulation and generalized hill climbing algorithms. Engineering Optimization 31: 247-260.

  Google Scholar 

• Johnson, A. W. 1996. Generalized hill climbing algorithms. Ph.D. Dissertation, Department of Industrial and Systems Engineering, Virginia Tech, Blacksburg, Virginia.

  Google Scholar 

• Johnson, A. W., and Jacobson, S. H. 2001a. A class of convergent generalized hill climbing algorithms. Applied Mathematics and Computation (to appear).

• Johnson, A. W., and Jacobson, S. H. 2001b. A general convergence result for hill climbing algorithms. Discrete Applied Mathematics (to appear).

• Lee, L. H., Lau, T. W. E., and Ho, Y. C. 1999. Explanation of goal softening in ordinal optimization. IEEE Transactions on Automatic Control 44(1): 94-99.

  Google Scholar 

• Medina, E. A. 1998. Cost function for discrete event dynamical system optimization program. Technical Report, Austral Engineering and Software, Inc., Athens, Ohio.

  Google Scholar 

• Reeves, C. R. 1993. Modern Heuristic Techniques for Combinatorial Problems. New York: John Wiley & Sons, Inc.

  Google Scholar 

• Yang, M. S., Lee, L. H., and Ho, Y. C. 1997. On stochastic optimization and its applications to manufacturing. Proceedings of AMS Conference on Stochastic Problems in Manufacturing, Lecture Notes in Applied Mathematics 33, pp. 317-331.

  Google Scholar 

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