Skip to main content

Advertisement

SpringerLink
Log in

Design of integrated information system and supply chain for selection of new facility and suppliers by a unique hybrid meta-heuristic computer simulation algorithm

  • ORIGINAL ARTICLE
  • Published:
The International Journal of Advanced Manufacturing Technology Aims and scope Submit manuscript

Abstract

This research concentrates on integrated modeling of supply chain and information system through a unique integrated meta-heuristic computer simulation algorithm. It uses computer simulation and genetic algorithm in order to select suppliers and new facilities by reducing delivery time and final production cost. To reach these goals, this research has simulated an actual case study with simulation and in the other stages, has moved forward to improve and optimize the objectives by focusing on selection of suppliers. It also uses the collective information to reduce total cycle time and cost simultaneously. Moreover, a dynamic model is designed to determine the status of new facilities. The dynamic model is solved by genetic algorithm focusing on the time and cost reduction as the main objectives of the problem. Results show the effectiveness of the integrated algorithm. This is the first study that uses a hybrid meta-heuristic approach for integrated design of information system and supply chain.

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

Similar content being viewed by others

References

  1. Ambrosino D, Scutella MG (2005) Distribution network design: new problems and related models. Eur J Oper Res 165:610–624

    Article  MATH  MathSciNet  Google Scholar 

  2. Amid A, Ghodsypour SH, O'Brien C (2006) Fuzzy multiobjective linear model for supplier selection in a supply chain. Int J Prod Econ 104(2):394–407

    Google Scholar 

  3. Amid A, Ghodsypour SH, O'Brien C (2011) Weighted max–min model for fuzzy multi-objective supplier selection in a supply chain. Int J Prod Econ 131(1):139–145

    Article  Google Scholar 

  4. Azadeh A, Haghnevis M, Khodadadegan M (2008) Design of the integrated information system, business and production process by simulation. J Am Soc Inf Sci Technol 59(2):216–234

    Article  Google Scholar 

  5. Baatz EB (1995) Best practice: the chain gang. CIO 8:46–52

    Google Scholar 

  6. Ballou RH (1968) Dynamic warehouse location analysis. J Mark Res 5:271–276

    Article  Google Scholar 

  7. Beamon BM (1998) Supply chain design and analysis: models and methods. Int J Prod Econ 55:281–294

    Article  Google Scholar 

  8. Bottani E, Rizzi A (2008) An adapted multi-criteria approach to suppliers and products selection—an application oriented to lead-time reduction. Int J Prod Econ 111(2):763–781

    Article  Google Scholar 

  9. Canel C, Khumawala BM, Law J, Loh A (2001) An algorithm for the capacitated, multi-commodity multi-period facility location problem. Comput Oper Res 28:411–427

    Article  MATH  MathSciNet  Google Scholar 

  10. Chang B, Hung HF (2010) A study of using RST to create the supplier selection model and decision-making rules. Expert Syst Appl 37:8284–8295

    Article  MathSciNet  Google Scholar 

  11. Che ZH, Wang HS (2008) Supplier selection and supply quantity allocation of common and non-common parts with multiple criteria under multiple products. Comput Ind Eng 55(1):110–133

    Article  Google Scholar 

  12. Chen YJ (2011) Structured methodology for supplier selection and evaluation in a supply chain. Inf Sci 181(9):1651–1670

    Article  Google Scholar 

  13. Christanthi A (2001) Information systems: what sort of science is it? Omega 28(5):567–579

    Google Scholar 

  14. Cordeau JF, Pasin F, Solomon MM (2006) An integrated model for logistics network design. Ann Oper Res 1:59–82

    Article  MathSciNet  Google Scholar 

  15. Cortinhal MJ, Captivo ME (2003) Upper and lower bounds for the single source capacitated location problem. Eur J Oper Res 151:333–351

    Article  MATH  MathSciNet  Google Scholar 

  16. Dahal KP, Galloway SJ, Burt GM, McDonald JR (2001) Generation scheduling using genetic algorithm based hybrid techniques. LESCOPE '01, Conference on 107 Large Engineering Systems in Power Engineering, pp. 74–78

  17. Daskin M, Snyder L, Berger R (2005) Logistics Systems: Design and Optimization. Chapter 2, Springer US, pp 39–65

  18. Dias J, Captivo ME, Climaco J (2006) Capacitated dynamic location problems with opening, closure and reopening of facilities. IMA J Manag Math 4:317–348

    Article  MathSciNet  Google Scholar 

  19. Farmer D (1997) Purchasing myopia – revisited. Eur J Purch Supply Manag 3:1–8

    Article  MathSciNet  Google Scholar 

  20. Farzipoor Saen R (2010) Restricting weights in supplier selection decisions in the presence of dual-role factors. Appl Math Model 34:2820–2830

    Article  MATH  MathSciNet  Google Scholar 

  21. Feng B, Fan ZP, Zhili Y (2011) A decision method for supplier selection in multi-service outsourcing. Int J Prod Econ 132:240–250

    Article  Google Scholar 

  22. Filho VJMF, Galvão RD (1998) A tab u search heuristic for the concentrator location problem. Locat Sci 6:189–209

    Article  Google Scholar 

  23. Goldberg DE (1989) Genetic algorithms in search, optimization, and machine learning. Addison-Wesley, Reading

    MATH  Google Scholar 

  24. Lee HL, Padmanabhan V, Whang S (1997) Information distortion in a supply chain: the bullwhip effect. Manag Sci 43:546–559

    Article  MATH  Google Scholar 

  25. Ha SH, Krishnan R (2008) A hybrid approach to supplier selection for the maintenance of a competitive supply chain. Expert Syst Appl 34(2):1303–1311

    Article  Google Scholar 

  26. Hamer-Lavoie G, Cordeau JF (2006) Un modè le pour la conception d'un re´seau de distribution avec localisation, affectation et stocks. INFOR 44:99–115

    MathSciNet  Google Scholar 

  27. Haralambos S, Chris DT (2008) Dynamic modeling and control of supply chain system: a review. Comput Oper Res 35:3530–3561

    Article  MATH  Google Scholar 

  28. Harland CM (1996) Supply chain management. Relationships, and networks. Br J Manag 7:68–80

    Google Scholar 

  29. He Y, Hui C-W (2010) A binary coding genetic algorithm for multi-purpose process scheduling: a case study. Chem Eng Sci 65(16):4816–4828

    Article  Google Scholar 

  30. Hinojosa Y, Puerto J (2006) Dynamic supply chain design with inventory. Comput Oper Res 35:373–391

    Article  MathSciNet  Google Scholar 

  31. Hinojosa Y, Puerto J, Ferna FR (2000) A multi-period two-echelon multi-commodity capacitated plant location problem. Eur J Oper Res 123:271–291

    Article  MATH  Google Scholar 

  32. Hirschheim R, Klein H, Lyytinen K (1995) Information systems development and data modeling: conceptual and philosophical foundations. Cambridge University Press, p 289

  33. Hou J, Su D (2006) Integration of Web Services technology with business models within the total product design process for supplier selection. Comput Ind 58(8–9):797–808

    Article  Google Scholar 

  34. Hyun JK, Gerald WE (2007) A genetic algorithm-based heuristic for the dynamic integrated forward/reverse logistics network for 3PLs. Comput Oper Res 34:346–366

    Article  MATH  Google Scholar 

  35. Inman RA, Hubler JH (1992) Certify the process, not just the product. Prod Invent Manag J 33:11–14

    Google Scholar 

  36. Jaramillio JH, Bhadury J, Batta R (2002) On the use of genetic algorithms to solve location problems. Comput Oper Res 29:761–779

    Article  MathSciNet  Google Scholar 

  37. Jardin A, Dejax P, Péton O (2006) A dynamic model for the strategic design of complex supply chains. Research Report 06/4/AUTO, Ecole des Mines de Nantes-IRCCyN

  38. Jayaram J, Vickery SK, Droge C (1999) An empirical study of time-based competition in the North America automotive supplier industry. Int J Oper Prod Man 19(10):1010–1033

    Google Scholar 

  39. Kokangul A, Susuz Z (2009) Integrated analytical hierarch process and mathematical programming to supplier selection problem with quantity discount. Appl Math Model 33:1417–1429

    Article  MATH  MathSciNet  Google Scholar 

  40. Krarup J, Pruzan PM (1983) The simple plant location problem: survey and synthesis. Eur J Oper Res 12:36–81

    Article  MATH  MathSciNet  Google Scholar 

  41. Lam K-C, Tao R, Lam MC (2010) A material supplier selection model for property developers using Fuzzy Principal Component Analysis. Autom Constr 19(5):608–618

    Article  Google Scholar 

  42. Li L, Zabinsky ZB (2011) Incorporating uncertainty into a supplier selection problem. Int J Prod Econ 134:344–356

    Article  Google Scholar 

  43. Luis P, Jose ML (2007) Capturing dynamics in integrated supply chain management. Comput Chem Eng 32(11):2582–2605

    Google Scholar 

  44. Luo X, Wu C, Rosenberg D, Barnes D (2009) Supplier selection in agile supply chains: an information-processing model and an illustration. J Purch Supply Manag 15(4):249–262

    Article  Google Scholar 

  45. Martel A (2005) The design of production–distribution networks: A mathematical programming approach. In: Geunes J, Pardalos PM (eds) Supply Chain Optimization, Springer, Berlin et al., pp 265–306

  46. Melachrinoudis E, Min H (2000) The dynamic relocation and phase-out of a hybrid, two-echelon plant/warehousing facility: a multiple objective approach. Eur J Oper Res 123:1–15

    Article  MATH  Google Scholar 

  47. Melkote S, Daskin MS (2001) Theory and methodology facility location/network design problems. Eur J Oper Res 129:481–495

    Google Scholar 

  48. Melo MT, Nickel S, Saldanha da Gama F (2005) Dynamic multi-commodity capacitated facility location: a mathematical modelling framework for strategic supply chain planning. Comput Oper Res 33:181–208

    Article  Google Scholar 

  49. Ongsakal W, Ruangpayoongsak N (2001) Constrained dynamic economic dispatch by simulated annealing/genetic algorithms. Power Industry Computer Applications, 207–212

  50. Paquet M, Martel A, Desaulniers G (2004) Including technology selection decisions in manufacturing network design models. Int J Comput Integr Manuf 17(2):117–125

    Article  Google Scholar 

  51. Geunes J, Pardalos PM (eds) Supply Chain Optimization. Springer, Berlin, pp 265–306

  52. Phoung NT, Nathalia B (2007) A dynamic model for facility location in the design of supply chain. Int J Prod Econ 113:678–693

    Google Scholar 

  53. Pritsker AB (1990) Papers, experiences and perspectives. Systems Publishing Corporation, Lafayette

    Google Scholar 

  54. Pritsker AB, Oreilly JJ, LaVal DK (1997) Simulation with Visual Slam and AweSim. John Wiley, New York

    Google Scholar 

  55. Pritsker AB, Sigal CE, Hammesfahr RDJ (1989) Network models for decision support. Prentice-Hall, New York

    Google Scholar 

  56. Shemshadi A, Shirazi H, Toreihi M, Tarokh MJ (2011) A fuzzy VIKOR method for supplier selection based on entropy measure for objective weighting. Expert Syst Appl 38(10):12160–12167

    Article  Google Scholar 

  57. Tsai YL, Yang YJ, Lin C (2010) A dynamic decision approach for supplier selection using ant colony system. Expert Syst Appl 37:8313–8321

    Article  Google Scholar 

  58. Tseng M-L, Chiang JH, Lan AW (2009) Selection of optimal supplier in supply chain management strategy with analytic network process and Choquet integral. Comput Ind Eng 57(1):330–340

    Article  Google Scholar 

  59. Ustun O, Demirtas EA (2007) Multi-period lot-sizing with supplier selection using achievement scalarizing functions. Comput Ind Eng 54(4):918–931

    Article  Google Scholar 

  60. Vanteddu G, Chinnam RB, Gushikin O (2009) Supply chain focus dependent supplier selection problem. Int J Prod Econ 129(1):204–216

    Article  Google Scholar 

  61. Vila D, Martel A, Beauregard R (2006) Designing logistics networks in divergent process industries: a methodology and its application to the lumber industry. Int J Prod Econ 102(2):358–378

    Article  Google Scholar 

  62. Wikipedia (2004) Genetic algorithm. Available from URL: http://en.wikipedia.org/wiki/Genetic_algorithm

  63. Wu WY, Sukoco BM, Li CY, Chen SH (2009) An integrated multi-objective decision-making process for supplier selection with bundling problem. Expert Syst Appl 36:2327–2337

    Article  Google Scholar 

  64. Zachman JA (1987) A framework for information system architecture. IBM Syst J 26(3):276–292

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. School of Industrial and Systems Engineering, College of Engineering, University of Tehran, Tehran, Iran

    A. Azadeh, A. Keramati, A. Karimi & P. Pourhaji

  2. School of Industrial Engineering, College of Engineering, University of Yazd, Yazd, Iran

    Z. Jiryaei Sharahi

Authors
  1. A. Azadeh
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. A. Keramati
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. A. Karimi
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Z. Jiryaei Sharahi
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. P. Pourhaji
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to A. Azadeh.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Azadeh, A., Keramati, A., Karimi, A. et al. Design of integrated information system and supply chain for selection of new facility and suppliers by a unique hybrid meta-heuristic computer simulation algorithm. Int J Adv Manuf Technol 71, 775–793 (2014). https://doi.org/10.1007/s00170-013-5417-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00170-013-5417-8

Keywords

Search

Navigation