Skip to main content

2015 | OriginalPaper | Buchkapitel

27. Exploring Pareto Frontiers in the Response Surface Methodology

verfasst von : Nuno Ricardo Costa, João Alves Lourenço

Erschienen in: Transactions on Engineering Technologies

Verlag: Springer Netherlands

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Abstract

Multiple response optimization problems have many optimal solutions that impact differently on process or product. Some of these solutions lead to operation conditions more hazardous, more costly or more difficult to implement and control. Therefore, it is useful for the decision-maker to use methods capable of capturing solutions evenly distributed along the Pareto frontier. Three examples were used to evaluate the ability of three methods built on different approaches for depicting the Pareto frontier. Limitations of a desirability-based method are illustrated whereas the consistent performance of an easy-to-use global criterion gives confidence to use it in real-life problems developed under the Response Surface Methodology framework, as alternative to the sophisticated physical programming method.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Literatur
1.
Zurück zum Zitat Myers, R., Montgomery, D., Anderson-Cook, C.: Response Surface Methodology: Process and Product Optimization Using Designed Experiments, 3rd edn. Wiley, Hoboken (2009)MATH Myers, R., Montgomery, D., Anderson-Cook, C.: Response Surface Methodology: Process and Product Optimization Using Designed Experiments, 3rd edn. Wiley, Hoboken (2009)MATH
2.
Zurück zum Zitat Costa, N., Lourenço, J., Pereira, Z.: Desirability function approach: a review and performance evaluation in adverse conditions. Chemom. Intell. Lab. Syst. 107, 234–244 (2011)CrossRef Costa, N., Lourenço, J., Pereira, Z.: Desirability function approach: a review and performance evaluation in adverse conditions. Chemom. Intell. Lab. Syst. 107, 234–244 (2011)CrossRef
3.
Zurück zum Zitat Derringer, G., Suich, R.: Simultaneous optimization of several response variables. J. Qual. Technol. 12, 214–218 (1980) Derringer, G., Suich, R.: Simultaneous optimization of several response variables. J. Qual. Technol. 12, 214–218 (1980)
4.
Zurück zum Zitat Derringer, G.: A balancing act: optimizing a product’s properties. Qual. Prog. 27, 51–58 (1994) Derringer, G.: A balancing act: optimizing a product’s properties. Qual. Prog. 27, 51–58 (1994)
5.
Zurück zum Zitat Das, P., Sengupta, S.: Composite desirability index in cases of negative and zero desirability. J. Manag. Resour. 10, 25–38 (2010) Das, P., Sengupta, S.: Composite desirability index in cases of negative and zero desirability. J. Manag. Resour. 10, 25–38 (2010)
6.
Zurück zum Zitat Murphy, T., Tsui, K., Allen, J.: A review of robust design methods for multiple responses. Res. Eng. Des. 15, 201–215 (2005)CrossRef Murphy, T., Tsui, K., Allen, J.: A review of robust design methods for multiple responses. Res. Eng. Des. 15, 201–215 (2005)CrossRef
7.
Zurück zum Zitat Ko, Y., Kim, K., Jun, C.: A new loss function-based method for multiresponse optimization. J. Qual. Technol. 37, 50–59 (2005) Ko, Y., Kim, K., Jun, C.: A new loss function-based method for multiresponse optimization. J. Qual. Technol. 37, 50–59 (2005)
8.
Zurück zum Zitat Pignatiello, J.: Strategies for robust multi-response quality engineering. IIE Trans. 25, 5–15 (1993)CrossRef Pignatiello, J.: Strategies for robust multi-response quality engineering. IIE Trans. 25, 5–15 (1993)CrossRef
9.
Zurück zum Zitat Vining, G.: A compromise approach to multiresponse optimization. J. Qual. Technol. 30, 309–313 (1998) Vining, G.: A compromise approach to multiresponse optimization. J. Qual. Technol. 30, 309–313 (1998)
10.
Zurück zum Zitat Köksoy, O.: A nonlinear programming solution to robust multi-response quality problem. Appl. Math. Comput. 196, 603–612 (2008)MathSciNetCrossRefMATH Köksoy, O.: A nonlinear programming solution to robust multi-response quality problem. Appl. Math. Comput. 196, 603–612 (2008)MathSciNetCrossRefMATH
11.
Zurück zum Zitat Pal, S., Gauri, S.: Assessing effectiveness of the various performance metrics for multi-response optimization using multiple regression. Comput. Ind. Eng. 59, 976–985 (2010)CrossRef Pal, S., Gauri, S.: Assessing effectiveness of the various performance metrics for multi-response optimization using multiple regression. Comput. Ind. Eng. 59, 976–985 (2010)CrossRef
12.
Zurück zum Zitat Tong, L.-I., Wang, C.-H.: Multi-response optimisation using principal component analysis and grey relational analysis. Int. J. Ind. Eng. 9, 343–350 (2002) Tong, L.-I., Wang, C.-H.: Multi-response optimisation using principal component analysis and grey relational analysis. Int. J. Ind. Eng. 9, 343–350 (2002)
13.
Zurück zum Zitat Liao, H.-C.: Multi-response optimization using weighted principal component. Int. J. Adv. Manuf. Technol. 27, 720–725 (2006)CrossRef Liao, H.-C.: Multi-response optimization using weighted principal component. Int. J. Adv. Manuf. Technol. 27, 720–725 (2006)CrossRef
14.
Zurück zum Zitat Awad, M., Kovach, J.: Multiresponse optimization using multivariate process capability index. Qual. Reliab. Eng. Int. 27, 465–477 (2011)CrossRef Awad, M., Kovach, J.: Multiresponse optimization using multivariate process capability index. Qual. Reliab. Eng. Int. 27, 465–477 (2011)CrossRef
15.
Zurück zum Zitat Kwak, D.-S., Kim, K.-J., Lee, M.-S.: Multistage PRIM: patient rule induction method for optimisation of a multistage manufacturing process. Int. J. Prod. Res. 48, 3461–3473 (2010)CrossRefMATH Kwak, D.-S., Kim, K.-J., Lee, M.-S.: Multistage PRIM: patient rule induction method for optimisation of a multistage manufacturing process. Int. J. Prod. Res. 48, 3461–3473 (2010)CrossRefMATH
16.
Zurück zum Zitat Al-Refaie, A.: Optimizing performance with multiple responses using cross-evaluation and aggressive formulation in data envelopment analysis. IIE Trans. 44, 262–276 (2012)CrossRef Al-Refaie, A.: Optimizing performance with multiple responses using cross-evaluation and aggressive formulation in data envelopment analysis. IIE Trans. 44, 262–276 (2012)CrossRef
17.
Zurück zum Zitat Govindaluri, S., Cho, B.: Robust design modeling with correlated quality characteristics using a multicriteria decision framework. Int. J. Adv. Manuf. Technol. 32, 423–433 (2007)CrossRef Govindaluri, S., Cho, B.: Robust design modeling with correlated quality characteristics using a multicriteria decision framework. Int. J. Adv. Manuf. Technol. 32, 423–433 (2007)CrossRef
18.
Zurück zum Zitat Kazemzadeh, B., Bashiri, M., Atkinson, A., Noorossana, R.: A general framework for multiresponse optimization problems based on goal programming. Eur. J. Oper. Res. 189, 421–429 (2008)MathSciNetCrossRefMATH Kazemzadeh, B., Bashiri, M., Atkinson, A., Noorossana, R.: A general framework for multiresponse optimization problems based on goal programming. Eur. J. Oper. Res. 189, 421–429 (2008)MathSciNetCrossRefMATH
19.
Zurück zum Zitat Messac, A.: Physical programming: effective optimization for computational design. AIAA J. 34, 149–158 (1996)CrossRefMATH Messac, A.: Physical programming: effective optimization for computational design. AIAA J. 34, 149–158 (1996)CrossRefMATH
20.
Zurück zum Zitat Chen, W., Sahai, A., Messac, A., Sundararaj, G.: Exploring the effectiveness of physical programming in robust design. J. Mech. Des. 122, 155–163 (2000)CrossRef Chen, W., Sahai, A., Messac, A., Sundararaj, G.: Exploring the effectiveness of physical programming in robust design. J. Mech. Des. 122, 155–163 (2000)CrossRef
21.
Zurück zum Zitat Peterson, J., Miró-Quesada, G., Del Castillo, E.: A bayesian reliability approach to multiple response optimization with seemingly unrelated regression models. Qual. Technol. Quant. Manag. 6, 353–369 (2009) Peterson, J., Miró-Quesada, G., Del Castillo, E.: A bayesian reliability approach to multiple response optimization with seemingly unrelated regression models. Qual. Technol. Quant. Manag. 6, 353–369 (2009)
22.
Zurück zum Zitat Dächert, K., Gorski, J., Klamroth, K.: An augmented weighted Tchebycheff method with adaptively chosen parameters for discrete bicriteria optimization problems. Comput. Oper. Res. 39, 2929–2943 (2012)MathSciNetCrossRef Dächert, K., Gorski, J., Klamroth, K.: An augmented weighted Tchebycheff method with adaptively chosen parameters for discrete bicriteria optimization problems. Comput. Oper. Res. 39, 2929–2943 (2012)MathSciNetCrossRef
23.
Zurück zum Zitat Lee, D., Jeong, I., Kim, K.: A posterior preference articulation approach to dual response surface optimization. IIE Trans. 42, 161–171 (2010)CrossRef Lee, D., Jeong, I., Kim, K.: A posterior preference articulation approach to dual response surface optimization. IIE Trans. 42, 161–171 (2010)CrossRef
24.
Zurück zum Zitat Lee, D., Kim, K., Köksalan, M.: An interactive method to multiresponse surface optimization based on pairwise comparisons. IIE Trans. 44, 13–26 (2012)CrossRef Lee, D., Kim, K., Köksalan, M.: An interactive method to multiresponse surface optimization based on pairwise comparisons. IIE Trans. 44, 13–26 (2012)CrossRef
25.
Zurück zum Zitat Ardakani, M., Wulff, S.: An overview of optimization formulations for multiresponse surface problems. Qual. Reliab. Eng. Int. 29, 3–16 (2013)CrossRef Ardakani, M., Wulff, S.: An overview of optimization formulations for multiresponse surface problems. Qual. Reliab. Eng. Int. 29, 3–16 (2013)CrossRef
26.
Zurück zum Zitat Costa, N., Lourenço, J.: Optimization criteria ability to depict Pareto frontiers. Lecture Notes in Engineering and Computer Science: Proceedings of The World Congress on Engineering 2014, WCE 2014, pp. 958–961. London, UK (2014) Costa, N., Lourenço, J.: Optimization criteria ability to depict Pareto frontiers. Lecture Notes in Engineering and Computer Science: Proceedings of The World Congress on Engineering 2014, WCE 2014, pp. 958–961. London, UK (2014)
27.
Zurück zum Zitat Costa, N., Lourenço, J., Pereira, Z.: Multiresponse optimization and Pareto frontiers. Qual. Reliab. Eng. Int. 28, 701–712 (2011)CrossRef Costa, N., Lourenço, J., Pereira, Z.: Multiresponse optimization and Pareto frontiers. Qual. Reliab. Eng. Int. 28, 701–712 (2011)CrossRef
28.
Zurück zum Zitat Köksoy, O., Doganaksoy, N.: Joint optimization of mean and standard deviation using response surface methods. J. Qual. Technol. 35, 239–252 (2003) Köksoy, O., Doganaksoy, N.: Joint optimization of mean and standard deviation using response surface methods. J. Qual. Technol. 35, 239–252 (2003)
29.
Zurück zum Zitat Ch’ng, C., Quah, S., Low, H.: A new approach for multiple-response optimization. Qual. Eng. 17, 621–626 (2005)CrossRef Ch’ng, C., Quah, S., Low, H.: A new approach for multiple-response optimization. Qual. Eng. 17, 621–626 (2005)CrossRef
30.
Zurück zum Zitat Costa, N., Pereira, Z.: Multiple response optimization: a global criterion-based method. J. Chemometr. 24, 333–342 (2010)CrossRef Costa, N., Pereira, Z.: Multiple response optimization: a global criterion-based method. J. Chemometr. 24, 333–342 (2010)CrossRef
31.
Zurück zum Zitat Messac, A., Mattson, C.: Generating well-distributed sets of Pareto points for engineering design using physical programming. Optim. Eng. 3, 431–450 (2002)CrossRefMATH Messac, A., Mattson, C.: Generating well-distributed sets of Pareto points for engineering design using physical programming. Optim. Eng. 3, 431–450 (2002)CrossRefMATH
33.
Zurück zum Zitat Messac, A., Melachrinoudis, E., Sukam, C.: Mathematical and pragmatic perspectives of physical programming. AIAA J. 39, 885–893 (2001)CrossRef Messac, A., Melachrinoudis, E., Sukam, C.: Mathematical and pragmatic perspectives of physical programming. AIAA J. 39, 885–893 (2001)CrossRef
34.
Zurück zum Zitat Yuan, Y., Ling, Z., Gao, C., Cao, J.: Formulation and application of weight-function-based physical programming. Eng. Optim. 46, 1628–1650 (2014)CrossRef Yuan, Y., Ling, Z., Gao, C., Cao, J.: Formulation and application of weight-function-based physical programming. Eng. Optim. 46, 1628–1650 (2014)CrossRef
35.
Zurück zum Zitat Martínez, M., Sanchis, J., Blasco, X.: Integrated multiobjective optimization and a priori preferences using genetic algorithms. Inform. Sci. 178, 931–951 (2008)MathSciNetCrossRefMATH Martínez, M., Sanchis, J., Blasco, X.: Integrated multiobjective optimization and a priori preferences using genetic algorithms. Inform. Sci. 178, 931–951 (2008)MathSciNetCrossRefMATH
36.
Zurück zum Zitat Martínez, M., Sanchis, J., Blasco, X.: Multi-objective engineering design using preferences. Eng. Optim. 40, 253–269 (2008)CrossRef Martínez, M., Sanchis, J., Blasco, X.: Multi-objective engineering design using preferences. Eng. Optim. 40, 253–269 (2008)CrossRef
37.
Zurück zum Zitat Sanchis, J., Martínez, M., Blasco, X., Reynoso-Meza, G.: Modelling preferences in multi-objective engineering design. Eng. Appl. Artif. Intel. 23, 1255–1264 (2010)CrossRef Sanchis, J., Martínez, M., Blasco, X., Reynoso-Meza, G.: Modelling preferences in multi-objective engineering design. Eng. Appl. Artif. Intel. 23, 1255–1264 (2010)CrossRef
38.
Zurück zum Zitat Utyuzhnikov, S., Fantini, P., Guenov, M.: A method for generating a well-distributed Pareto set in nonlinear multiobjective optimization. J. Comput. Appl. Math. 223, 820–841 (2009)MathSciNetCrossRefMATH Utyuzhnikov, S., Fantini, P., Guenov, M.: A method for generating a well-distributed Pareto set in nonlinear multiobjective optimization. J. Comput. Appl. Math. 223, 820–841 (2009)MathSciNetCrossRefMATH
39.
Zurück zum Zitat Chen, W., Wiecek, M., Zhang, J.: Quality utility: a compromise programming approach to robust design. J. Mech. Des. 121, 179–187 (1999)CrossRef Chen, W., Wiecek, M., Zhang, J.: Quality utility: a compromise programming approach to robust design. J. Mech. Des. 121, 179–187 (1999)CrossRef
40.
Zurück zum Zitat Das, I., Dennis, J.: A closer look at drawbacks of minimizing weighted-sums of objectives for Pareto set generation in multicriteria optimization problems. Struct. Optim. 14, 63–69 (1997)CrossRef Das, I., Dennis, J.: A closer look at drawbacks of minimizing weighted-sums of objectives for Pareto set generation in multicriteria optimization problems. Struct. Optim. 14, 63–69 (1997)CrossRef
41.
Zurück zum Zitat Marler, R., Arora, J.: The weighted sum method for multi-objective optimization: some insights. Struct. Multidiscip. Optim. 41, 853–862 (2010)MathSciNetCrossRefMATH Marler, R., Arora, J.: The weighted sum method for multi-objective optimization: some insights. Struct. Multidiscip. Optim. 41, 853–862 (2010)MathSciNetCrossRefMATH
42.
Zurück zum Zitat Athan, T., Papalambros, P.: A note on weighted criteria methods for compromise solutions in multi-objective optimization. Eng. Optim. 27, 155–176 (1996)CrossRef Athan, T., Papalambros, P.: A note on weighted criteria methods for compromise solutions in multi-objective optimization. Eng. Optim. 27, 155–176 (1996)CrossRef
43.
Zurück zum Zitat Messac, A., Sundararaj, G., Tappeta, R., Renaud, J.: Ability of objective functions to generate points on non-convex Pareto frontiers. AIAA J. 38, 1084–1091 (2000)CrossRef Messac, A., Sundararaj, G., Tappeta, R., Renaud, J.: Ability of objective functions to generate points on non-convex Pareto frontiers. AIAA J. 38, 1084–1091 (2000)CrossRef
44.
Zurück zum Zitat Marler, R., Arora, J.: Survey of multi-objective optimization methods for engineering. Struct. Multidiscip. Optim. 26, 369–395 (2004)MathSciNetCrossRefMATH Marler, R., Arora, J.: Survey of multi-objective optimization methods for engineering. Struct. Multidiscip. Optim. 26, 369–395 (2004)MathSciNetCrossRefMATH
45.
Zurück zum Zitat Sanchis, J., Martínez, M., Blasco, X.: Multi-objective engineering design using preferences. Eng. Optim. 40, 253–269 (2008)CrossRef Sanchis, J., Martínez, M., Blasco, X.: Multi-objective engineering design using preferences. Eng. Optim. 40, 253–269 (2008)CrossRef
46.
Zurück zum Zitat Martínez, M., Sanchis, J., Blasco, X.: Multiobjective controller design handling human preferences. Eng. Appl. Artif. Intel. 19, 927–938 (2006)CrossRef Martínez, M., Sanchis, J., Blasco, X.: Multiobjective controller design handling human preferences. Eng. Appl. Artif. Intel. 19, 927–938 (2006)CrossRef
Metadaten
Titel
Exploring Pareto Frontiers in the Response Surface Methodology
verfasst von
Nuno Ricardo Costa
João Alves Lourenço
Copyright-Jahr
2015
Verlag
Springer Netherlands
DOI
https://doi.org/10.1007/978-94-017-9804-4_27

    Marktübersichten

    Die im Laufe eines Jahres in der „adhäsion“ veröffentlichten Marktübersichten helfen Anwendern verschiedenster Branchen, sich einen gezielten Überblick über Lieferantenangebote zu verschaffen.