Skip to main content
SpringerLink
Log in

Optimisation of product family design with consideration of supply risk and discount

  • Original Paper
  • Published:
Research in Engineering Design Aims and scope Submit manuscript

Abstract

Optimisation of product family design has been emphasised and studied for many years. However, previous studies only took overall cost or profit as an optimisation objective, but ignored the supply risk of a product family. Moreover, the discount associated with the bidding price, which is common in practice, was not considered in the modelling. In this paper, we propose a new multi-objective optimisation approach integrating supplier selection into product family design. In our optimisation model, not only the profit but also the supply risk of a product family is formulated as optimisation objectives. Consequently, we can evaluate and optimise a product family from many perspectives. In addition, as a bidding price discount may affect product family’s configuration and supplier selection, we include linear piecewise discount of bidding prices from suppliers in our optimisation model. The NSGA-II algorithm is developed to achieve Pareto non-dominated solutions of the multi-objective optimisation model. Sensitivity analysis on the model parameters is performed, and several managerial insights for enterprises are achieved in the case study of a printing calculator product.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12

Similar content being viewed by others

References

  • Aissaoui N, Haouari M, Hassini E (2007) Supplier selection and order lot sizing modeling: a review. Comput Oper Res 34(12):3516–3540

    Article  MATH  Google Scholar 

  • Arunkumar N, Karunamoorthy L, Anand S, Babu TR (2006) Linear approach for solving a piecewise linear vendor selection problem of quantity discounts using lexicographic method. Int J Adv Manuf Technol 28(11–12):1254–1260

    Article  Google Scholar 

  • Balakrishnan N, Chakravarty AK (2008) Product design with multiple suppliers for component variants. Int J Prod Econ 112(2):723–741

    Article  Google Scholar 

  • Ben-Akiva M, Lerman S (1985) Discrete choice analysis: theory and application to travel demand. The MIT Press, Cambridge

    Google Scholar 

  • Cao Y, Luo XG, Kwong CK, Tang JF (2012) Joint optimization of product family design and supplier selection under multinomial logit consumer choice rule. Concurr Eng 20(4):346–357

    Article  Google Scholar 

  • Chamodrakas I, Batis D, Martakos D (2010) Supplier selection in electronic marketplaces using satisficing and fuzzy AHP. Expert Syst Appl 37(1):490–498

    Article  Google Scholar 

  • Crama Y, Pascual R, Torres A (2004) Optimal procurement decisions in the presence or total quantity discounts and alternative product recipes. Eur J Op Res 159(2):364–378

    Article  MATH  Google Scholar 

  • De Boer L, Labro E, Morlacchi P (2001) A review of methods supporting supplier selection. Eur J Purch Supply Manag 7(2):75–89

    Article  Google Scholar 

  • Deb K, Pratap A, Agarwal S, Meyarivan T (2002) A fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE Trans Evolut Comput 6(2):182–197

    Article  Google Scholar 

  • Dobson G, Kalish S (1993) Heuristics for pricing and positioning a product-line using conjoint and cost data. Manag Sci 39(2):160–175

    Article  Google Scholar 

  • Erixon G (1996) Design for modularity. In: Huang GQ (ed) Design for X: concurrent engineering imperatives. Chapman & Hall, NewYork, pp 356–379

    Chapter  Google Scholar 

  • Esterman M, Ishii K (2001) Concurrent product development across the supply chain: development of integrator/supplier risk and coupling indices. In: Proceedings of the ASME design engineering technical conference, vol 3. pp 313–322

  • Esterman M Jr, Ishii K (2005) The development of project risk metrics for robust concurrent product development (CPD) across the supply chain. Concurr Eng Res Appl 13(2):85–94

    Article  Google Scholar 

  • Fogliattoa FS, da Silveira GJC, Borenstein D (2012) The mass customization decade: an updated review of the literature. Int J Prod Econ 138(1):14–25

    Article  Google Scholar 

  • Fruchter GE, Fligler A, Winer RS (2006) Optimal product line design: genetic algorithm approach to mitigate cannibalization. J Optim Theory Appl 131(2):227–244

    Article  MathSciNet  MATH  Google Scholar 

  • Fujita K (2002) Product variety optimization under modular architecture. Comput Aided Des 34:953–965

    Article  Google Scholar 

  • Goldberg J, Zhu J (1989) Module design with substitute parts and multiple vendors. Eur J Op Res 41(3):335–346

    Article  Google Scholar 

  • Green PE, Krieger AM (1992) An application of a product positioning model to pharmaceutical products. Mark Sci 11:117–132

    Article  Google Scholar 

  • Gualandris J, Kalchschmidt M (2013) Product and process modularity: improving flexibility and reducing supplier failure risk. Int J Prod Res 51(19):5757–5770

    Article  Google Scholar 

  • Gupta S, Krishnan V (1999) Integrated component and supplier selection for a product family. Prod Op Manag 8(2):163–182

    Article  Google Scholar 

  • Hsu TH, Chu KM, Chan HC (2000) Fuzzy clustering on market segment. In: IEEE international conference on fuzzy systems, vol 2. San Antonio, pp 621–626

  • Huang GQ, Xin Yan Z, Lo VHY (2007) Integrated configuration of platform products and supply chains for mass customization: a game-theoretic approach. IEEE Trans Eng Manag 54(1):156–171

    Article  Google Scholar 

  • Hur D, Kang DJ, Kim BH (2007) Supplier bidding strategy based on non-cooperative game theory concepts in single auction power pools. Electr Power Syst Res 77(5–6):630–636

    Google Scholar 

  • Jiao J, Zhang Y (2005) Product portfolio planning with customer-engineering interaction. IIE Trans 37(9):801–814

    Article  Google Scholar 

  • Jiao JX, Simpson TW, Siddique Z (2007) Product family design and platform-based product development: a state-of-the-art review. J Intell Manuf 18(1):5–29

    Article  Google Scholar 

  • Kohli R, Sukumar R (1990) Heuristics for product-line design using conjoint analysis. Manag Sci 36(12):1464–1478

    Article  Google Scholar 

  • Kokangul A, Susuz Z (2009) Integrated analytical hierarch process and mathematical programming to supplier selection problem with quantity discount. Appl Math Model 33(14):17–29

    MathSciNet  Google Scholar 

  • Kuo RJ, Wang YC, Tien FC (2010) Integration of artificial neural network and MADA methods for green supplier selection. J Clean Prod 181(12):1161–1170

    Article  Google Scholar 

  • Lee BU, Kim CM, Park RH (2000) An orientation reliability matrix for the iterative closest point algorithm. IEEE Trans Pattern Anal Mach Intell 22(12):5–8

    MathSciNet  Google Scholar 

  • Li H, Guo G, Xu JP, Shen L, Yang J (2010) Supplier management model in collaborative product development. J Chongqing Univ 33(3):41–48

    Google Scholar 

  • Luo XG, Kwong CK, Tang JF, Deng F (2011) Integrating supplier selection in optimal product family design. Int J Prod Res 49(14):4195–4222

    Article  MATH  Google Scholar 

  • Ong S, Lin Q, Nee A (2006) Web-based configuration design system for product customization. Int J Prod Res 44(2):351–382

    Article  Google Scholar 

  • Pimmler TU, Eppinger SD (1994) Integration analysis of product decompositions. In: ASME design theory and methodology conference. Minneapolis

  • Pine B (1993) Mass customization: the new frontier in business competition. Harvard Business, Boston

    Google Scholar 

  • Ravindran R, Bilsel RU, Wadhwa V, Yang T (2010) Risk adjusted multicriteria supplier selection models with applications. Int J Prod Res 48(2):405–424

    Article  MATH  Google Scholar 

  • Sadrian AA, Yoon YS (1992) Business volume discount: a new perspective on discount pricing strategy. Int J Purch Mater Manag 28(7):43–46

    Google Scholar 

  • Silveira GD, Borenstein D, Fogliatto FS (2001) Mass customization: literature review and research directions. Int J Prod Econ 72(1):1–13

    Article  Google Scholar 

  • Simpson TW, Siddique Z, Jiao JX (2006) Product platform and product family design: methods and applications. Springer, New York

    Book  Google Scholar 

  • Steiner W, Hruschka H (2002) A probabilistic one-step approach to the optimal product line design problem using conjoint and cost data. In: Review of marketing science, working paper

  • Stone RB, Wood KL, Crawford RH (2000) A heuristic method for identifying modules for product architectures. Des Stud 21(1):5–31

    Article  Google Scholar 

  • Train KE (2003) Discrete choice methods with simulation. Cambridge University Press, Cambridge

    Book  MATH  Google Scholar 

  • Urban GL, Hauser JR (1993) Design and marketing of new products. Prentice Hall, Englewood Cliffs

    Google Scholar 

  • Weber CA, Current JR, Benton WC (1991) Vendor selection criteria and methods. Eur J Op Res 50(1):2–18

    Article  Google Scholar 

Download references

Acknowledgments

This work is financially supported by the National Science Foundation of China (NSFC Proj. 71171039 and 61273204). The authors would like to thank the Prof. Shixin Liu and Shu’an Liu for their suggestions. The authors would like to thank the anonymous reviewers for the constructive comments and suggestions.

Author information

Authors and Affiliations

  1. Department of Systems Engineering, School of Information, Northeastern University, Shenyang, Peoples’ Republic of China

    Xinggang Luo & Yan Cao

  2. Department of Mechanical Engineering, University of Kentucky, Lexington, KY, USA

    Wei Li

  3. Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, Peoples’ Republic of China

    C. K. Kwong

Authors
  1. Xinggang Luo
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Wei Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. C. K. Kwong
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Yan Cao
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Xinggang Luo.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Luo, X., Li, W., Kwong, C.K. et al. Optimisation of product family design with consideration of supply risk and discount. Res Eng Design 27, 37–54 (2016). https://doi.org/10.1007/s00163-015-0204-1

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00163-015-0204-1

Keywords

Search

Navigation