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Ant Colony Strategy and Desirability Function Approach for Continuous Correlated Multiple Response Optimization Problems

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Author Affiliations

  • 1Department of Statistics, Krishnagar Government College, West Bengal, India
  • 2Department of Mathematics, Krishnagar Government College, West Bengal, India

Res. J. Mathematical & Statistical Sci., Volume 4, Issue (8), Pages 10-14, September,12 (2016)

Abstract

In Quality Engineering and Management Field, multiple response optimization problems is critical and important area of research. These problems may be correlated or uncorrelated. For various multimodal single and multi-response optimization problems, meta-heuristics iterative search strategies provide satisfactory global solution. In this paper, ant colony optimization strategy with desirability function approach are used to optimize correlated multi-response problems. The multi-response optimization problems are modeling by using ordinary least-square regression.

References

  1. M. Dorigo (1992)., Optimization, Learning and Natural Algorithms., Ph.D. Thesis, ipartimento di Elettronica, Politecnico di Milano, Italy.
  2. Bilchev G. and Parmee I.C. (1995)., The ant colony metaphor for searching continuous design spaces., Lecture Notes in Computer Science, New York, Springer- Verlag, 993, 25-39.
  3. Wodrich M. and Bilchev G. (1997)., Cooperative distributed search: the ants way., Control Cybernetics, 26, 413.
  4. Mathur M., Karale S.B., Priye S., Jayaraman V.K. and Kulkarni B.D. (2000)., Ant colony approach to continuous function optimization., Ind. Eng. Chem. Res., 39, 3814-3822.
  5. Jayaraman V.K., Kulkarni B.D., Karale S. and Shelokar P. (2000)., Ant colony framework for optimal design and scheduling of batch plants., Computer and Chemical Engineering, 24, 1901-1912.
  6. Jayaraman V.K., Kulkarni B.D., Gupta K., Rajesh J. and Kusumaker H.S. (2001)., Dynamic optimization of fed-batch bioreactors using the ant algorithm., Biotechnol. Prog., 17, 81-88.
  7. Prabhaharan G., Asokan P. and Rajendran S. (2005)., Sensitivity-based conceptual design and tolerance allocation using the continuous ants colony algorithm (CACO)., Int J Adv Manuf Technol, 25, 516-526.
  8. Socha K. and Dorigo M. (2008)., Ant colony optimization for continuous domains., European Journal of Operation Research, 185, 1155-1173.
  9. Harrington E.C. (1965)., The desirability function., Industrial Quality Control, 21(10), 51-57.
  10. Derringer G. and Suich R. (1980)., Simultaneous optimization of several response variables., Journal of Quality Technology, 12(4), 214-219.
  11. Kim K.J. and Lin D.K.J. (2000)., Simultaneous optimization of mechanical properties of steel by maximizing exponential desirability functions., Journal of the Royal Statistical Society Applied Statistics Series C, 49(3), 311-325.
  12. Mukherjee I. (2006)., Modeling and optimization of abrasive metal cutting processes., Ph.D. Thesis, IIT Kharagpur, India.
  13. Shah H.K., Montgomery D.C. and Carlyle W.M. (2004)., Response surface modeling and optimization in multiresponse experiments using seemingly unrelated regressions., Quality Engineering, 16(3), 387-397.
  14. Khuri A.l. and Conlon M. (1981)., Simultaneous optimization of multiple responses represented by polynomial regression functions., Technometrices, 23(4), 363-375.