Advertisement

Soft Computing

, Volume 22, Issue 9, pp 2891–2905 | Cite as

Simultaneous selection of material and supplier under uncertainty in carton box industries: a fuzzy possibilistic multi-criteria approach

  • Sam Mosallaeipour
  • Ali Mahmoodirad
  • Sadegh Niroomand
  • Bela Vizvari
Methodologies and Application

Abstract

A critical problem in carton box production industries arises when size, amount and supplier of raw sheet are to be determined in an uncertain and competitive environment from sheet price point of view. This study introduces a multi-criteria mixed integer formulation to select size, amount and supplier of raw sheets used in a case study of carton box manufacturing sector in order to minimize objectives such as cost, wastage of sheets and surplus of carton boxes simultaneously. To respect the uncertain market, some parameters of the problem such as demand of the boxes, price of raw sheets are considered as fuzzy numbers. To cope with uncertainty of the introduced mathematical formulation, a possibilistic approach is applied to convert the fuzzy formulation to a crisp model. In order to tackle the multi-criteria crisp formulation, a new multi-objective solution approach is proposed to solve the problem in comparison with four multi-objective optimization approaches such as LH, TH, SO, and ABS methods of the literature. Computational experiments and sensitivity analysis which are performed on real numerical data given by study case show the superior performance of the proposed approach compared to the others.

Keywords

Fuzzy possibilistic approach Multi-criteria optimization Supplier and material selection Carton box industry 

Notes

Acknowledgements

The authors are grateful to the editors and the referees of the journal for their helpful and constructive comments that improved the quality of this paper. This study was not funded by any organization.

Compliance with ethical standards

Conflict of interest

Sam Mosallaeipour, Ali Mahmoodirad, Sadegh Niroomand, Bela Vizvari declare that they have no conflict of interest.

Ethical approval

This article does not contain any studies with human participants or animals performed by any of the authors.

References

  1. Abdollahi M, Arvan M, Razmi J (2015) An integrated approach for supplier portfolio selection: lean or agile? Expert Syst Appl 42(1):679–690CrossRefGoogle Scholar
  2. Alavidoost MH, Babazadeh H, Sayyari ST (2016) An interactive fuzzy programming approach for bi-objective straight and U-shaped assembly line balancing problem. Appl Soft Comput 40:221–235CrossRefGoogle Scholar
  3. Alp O, Tan T (2008) Tactical capacity management under capacity flexibility. IIE Trans 40(3):221–237CrossRefGoogle Scholar
  4. Alp O, Tim Huh W, Tan T (2013) Inventory control with multiple setup costs. Manuf Serv Oper Manage 16(1):89–103CrossRefGoogle Scholar
  5. Awasthi A, Chauhan SS, Goyal SK, Proth J-M (2009) Supplier selection problem for a single manufacturing unit under stochastic demand. Int J Prod Econ 117(1):229–233CrossRefGoogle Scholar
  6. Ayhan MB (2013) A fuzzy AHP approach for supplier selection problem: a case study in a gear Motor Company. Artif Intell. Retrieved from arXiv:1311.2886
  7. Batuhan M, Selcuk H (2015) A two stage approach for supplier selection problem in multi-item multi-supplier environment with quantity discounts. Comput Ind Eng 85:1–12CrossRefGoogle Scholar
  8. Cakravastia A, Toha IS, Nakamura N (2002) A two-stage model for the design of supply chain networks. Int J Prod Econ 80(3):231–248CrossRefGoogle Scholar
  9. Dubois D, Fargier H, Fortemps P (2003) Fuzzy scheduling: modelling flexible constraints vs. coping with incomplete knowledge. Eur J Oper Res 147:231–252MathSciNetCrossRefzbMATHGoogle Scholar
  10. El-Sayed M, Afia N, El-Kharbotly N (2010) A stochastic model for forward-reverse logistics network design under risk. Comput Ind Eng 58:423–431CrossRefGoogle Scholar
  11. Franco A, Jablonsky J, Leopold-Wildburger U, Montibeller G (2009) Feature cluster: facilitated problem structuring and decision analysis (EURO 2007). Eur J Oper Res 199(3):801–802CrossRefGoogle Scholar
  12. Fullér R, Canós-Darós L, Canós-Darós MJ (2012) Transparent fuzzy logic based methods for some human resources problems. Rev Electr Comun Trabajos ASEPUMA 13:27–41Google Scholar
  13. Fullér R, Majlender P (2004) On interactive fuzzy numbers. Fuzzy Sets Syst 143:355–369MathSciNetCrossRefzbMATHGoogle Scholar
  14. Gilmore PC, Gomory RE (1965) Multistage cutting stock problems of two and more dimensions. Oper Res 13(1):94–120CrossRefzbMATHGoogle Scholar
  15. Gabli M, Jaara EM, Mermri EB (2015) A possibilistic approach to UMTS base-station location problem. Soft Comput. doi: 10.1007/s00500-015-1658-9
  16. Hadi-Vencheh A, Mohamadghasemi A (2015) A new hybrid fuzzy multi-criteria decision making model for solving the material handling equipment selection problem. Int J Comput Integr Manuf 28(5):534–550CrossRefGoogle Scholar
  17. Hadi-Vencheh A, Rezaei Z, Razipour S (2014) Solving fully fuzzy multiple objective linear programming problems: a new perspective. J Soft Comput Appl 1–4Google Scholar
  18. Hazra J, Mahadevan B (2009) A procurement model using capacity reservation. Eur J Oper Res 193(1):303–316MathSciNetCrossRefzbMATHGoogle Scholar
  19. Jablonsky J (2007) Measuring the efficiency of production units by AHP models. Math Comput Model 46(7–8):1091–1098MathSciNetCrossRefzbMATHGoogle Scholar
  20. Jablonsky J (2014) MS Excel based software support tools for decision problems with multiple criteria. Proc Econ Finance 12:251–258CrossRefGoogle Scholar
  21. Jimenez M, Arenas M, Bilbao A, Rodriguez MV (2007) Linear programming with fuzzy parameters: an interactive method resolution. Eur J Oper Res 177:1599–1609MathSciNetCrossRefzbMATHGoogle Scholar
  22. Jimenez M (1996) Ranking fuzzy numbers through the comparison of its expected intervals. Int J Uncertain Fuzziness Knowl Based Syst 4(4):379–388MathSciNetCrossRefzbMATHGoogle Scholar
  23. Kovács G, Marian M (2002) Viability results in control of one-dimensional discrete time dynamical systems defined by a multi-function. Pure Math Appl 13(1–2):185–195MathSciNetGoogle Scholar
  24. Krajewski LJ, Ritzman LP (2001) Operations management: strategy and analysis. Prentice-Hall, Englewood CliffsGoogle Scholar
  25. Lai Y-J, Hwang C-L (1993) Possibilistic linear programming for managing interest rate risk. Fuzzy Sets Syst 54:135–146Google Scholar
  26. Listes O, Dekker R (2005) A stochastic approach to a case study for product recovery network design. Eur J Oper Res 160:268–287CrossRefzbMATHGoogle Scholar
  27. Moloudzadeh S, Allahviranloo T, Darabi P (2013) A new method for solving an arbitrary fully fuzzy linear system. Soft Comput 17(9):1725–1731CrossRefzbMATHGoogle Scholar
  28. Mula J, Poler R, Garcia JP (2006) MRP with flexible constraints: a fuzzy mathematical programming approach. Fuzzy Sets Syst 157:74–97MathSciNetCrossRefzbMATHGoogle Scholar
  29. Ozgen D, Gulsun B (2014) Combining possibilistic linear programming and fuzzy AHP for solving the multi-objective capacitated multi-facility location problem. Inf Sci 268:185–201MathSciNetCrossRefzbMATHGoogle Scholar
  30. Parra MA, Terol AB, Gladish BP, Rodriguez Uria MV (2005) Solving a multiobjective possibilistic problem through compromise programming. Eur J Oper Res 164:748–759MathSciNetCrossRefzbMATHGoogle Scholar
  31. Pishvaee MS, Torabi SA (2010) A possibilistic programming approach for closed-loop supply chain network design under uncertainty. Fuzzy Sets Syst 161:2668–2683MathSciNetCrossRefzbMATHGoogle Scholar
  32. Russo M, Sforza A, Sterle C (2014) An exact dynamic programming algorithm for large-scale unconstrained two-dimensional guillotine cutting problems. Comput Oper Res 50:97–114MathSciNetCrossRefzbMATHGoogle Scholar
  33. Salahshour S, Allahviranloo T (2013) Applications of fuzzy Laplace transforms. Soft Comput 17(1):145–158CrossRefzbMATHGoogle Scholar
  34. Salmasnia A, Khatami M, Baradaran Kazemzadeh R, Zegordi SH (2015) Bi-objective single machine scheduling problem with stochastic processing times. Top 23(1):275–297MathSciNetCrossRefzbMATHGoogle Scholar
  35. Selim H, Ozkarahan I (2008) A supply chain distribution network design model: an interactive fuzzy goal programming-based solution approach. Int J Adv Manuf Technol 36:401–418CrossRefGoogle Scholar
  36. Semwal VB, Chakraborty P, Nandi GC (2015a) Less computationally intensive fuzzy logic (type-1)-based controller for humanoid push recovery. Robot Auton Syst 63(1):122–135Google Scholar
  37. Semwal VB, Mondal K, Nandi GC (2015b) Robust and accurate feature selection for humanoid push recovery and classification: deep learning approach. Neural Comput Appl. doi: 10.1007/s00521-015-2089-3
  38. Singha J, Misra S, Laskar RH (2016) Effect of variation in gesticulation pattern in dynamic hand gesture recognition system. Neurocomputing 208:269–280CrossRefGoogle Scholar
  39. Tan T, Alp O (2009) An integrated approach to inventory and flexible capacity management subject to fixed costs and non-stationary stochastic demand. OR Spectrum 31(2):337–360MathSciNetCrossRefzbMATHGoogle Scholar
  40. Tan T, Alp O (2015) Optimal sourcing from alternative capacitated suppliers and general cost structures. Omega 58:26–32CrossRefGoogle Scholar
  41. Torabi SA, Hassini E (2008) An interactive possibilistic programming approach for multiple objective supply chain master planning. Fuzzy Sets Syst 159:193–214MathSciNetCrossRefzbMATHGoogle Scholar
  42. Wang JQ, Zhou P, Li KJ, Zhang HU, Chen XH (2014) Multi-criteria decision-making method based on normal intuitionistic fuzzy-induced generalized aggregation operator. Top 22(3):1103–1122MathSciNetCrossRefzbMATHGoogle Scholar
  43. Weber CA, Current JR, Benton WC (1991) Vendor selection criteria and methods. Eur J Oper Res 50(1):2–18CrossRefGoogle Scholar
  44. Zimmermann HJ (1978) Fuzzy programming and linear programming with several objective functions. Fuzzy Sets Syst 1:45–55MathSciNetCrossRefzbMATHGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2017

Authors and Affiliations

  1. 1.Department of Industrial EngineeringEastern Mediterranean UniversityFamagustaTurkey
  2. 2.Department of Mathematics, Masjed-Soleiman BranchIslamic Azad UniversityMasjed-SoleimanIran
  3. 3.Department of Industrial EngineeringFirouzabad Institute of Higher EducationFirouzabadIran

Personalised recommendations