Multiple Criteria Inventory Classification Approach Based on Differential Evolution and Electre III | SpringerLink
Skip to main content
Springer Nature Link
Log in

Multiple Criteria Inventory Classification Approach Based on Differential Evolution and Electre III

  • Conference paper
  • First Online:
Proceedings of the 16th International Conference on Hybrid Intelligent Systems (HIS 2016) (HIS 2016)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 552))

Included in the following conference series:

Abstract

The ABC classification represents one of the most frequently used analysis in production and inventory management domains. This analysis is applied to categorize a set of items in three predefined classes A, B and C, where each class follows a specific management and control policies, in order to generate companies financial well-being. This paper introduces a new approach for the multi-criteria inventory classification based on the hybridization of the Differential Evolution algorithm (DE) with the multi-criteria decision making method namely Electre III. The evolutionary algorithm (DE) attends to learn and optimize the Electre III input parameters (criteria weights). The Electre III method generates a ranking score for all the inventory items and an ABC distribution dispatches all these items into three ordered classes A, B, C, forming a complete classification. An inventory cost function is used thereafter to evaluate each established classification. This function is based on different inventory costs and service level measurement and also represents the objective function of our model, which consists of minimizing the inventory cost. The highlight of our proposed hybridization approach DE-Electre III is the exploitation of the robustness and efficiency of used techniques. Based on generated results, our model provided encouraging results in the ABC MCIC problem.

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

Access this chapter

Log in via an institution

Subscribe and save

Springer+ Basic
¥17,985 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
JPY 3498
Price includes VAT (Japan)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
JPY 22879
Price includes VAT (Japan)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
JPY 28599
Price includes VAT (Japan)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  1. Babai, M., Ladhari, T., Lajili, I.: On the inventory performance of multi-criteria classification methods: empirical investigation. Int. J. Prod. Res. 53(1), 279–290 (2015)

    Article  Google Scholar 

  2. Bhattacharya, A., Sarkar, B., Mukherjee, S.: Distance-based consensus method for ABC analysis. Int. J. Prod. Res. 45(15), 3405–3420 (2007)

    Article  MATH  Google Scholar 

  3. Braglia, M., Grassi, A., Montanari, R.: Multi-attribute classification method for spare parts inventory management. J. Qual. Maintenance Eng. 10(1), 55–65 (2004)

    Article  Google Scholar 

  4. Chen, J.: Peer-estimation for multiple criteria ABC inventory classification. Comput. Oper. Res. 38(12), 1784–1791 (2011)

    Article  MathSciNet  MATH  Google Scholar 

  5. Chen, J.X.: Multiple criteria ABC inventory classification using two virtual items. Int. J. Prod. Res. 50(6), 1702–1713 (2012)

    Article  Google Scholar 

  6. Figueira, J.R., Greco, S., Roy, B., Słowiński, R.: An overview of electre methods and their recent extensions. J. Multi-Criteria Decis. Anal. 20(1–2), 61–85 (2013)

    Article  Google Scholar 

  7. Flores, B., Olson, D., Dorai, V.: Management of multicriteria inventory classification. Math. Comput. Model. 16(12), 71–82 (1992)

    Article  MATH  Google Scholar 

  8. Gajpal, P., Ganesh, L., Rajendran, C.: Criticality analysis of spare parts using the analytic hierarchy process. Int. J. Prod. Econ. 35(1), 293–297 (1994)

    Article  Google Scholar 

  9. Güvenir, H.A.: A genetic algorithm for multicriteria inventory classification. In: Artificial Neural Nets and Genetic Algorithms, pp. 6–9. Springer (1995)

    Google Scholar 

  10. Guvenir, H.A., Erel, E.: Multicriteria inventory classification using a genetic algorithm. Eur. J. Oper. Res. 105(1), 29–37 (1998)

    Article  MATH  Google Scholar 

  11. Hadi-Vencheh, A.: An improvement to multiple criteria ABC inventory classification. Eur. J. Oper. Res. 201(3), 962–965 (2010)

    Article  MATH  Google Scholar 

  12. Hadi-Vencheh, A., Mohamadghasemi, A.: A fuzzy AHP-DEA approach for multiple criteria ABC inventory classification. Expert Syst. Appl. 38(4), 3346–3352 (2011)

    Article  Google Scholar 

  13. Kabir, G.: Multiple criteria inventory classification under fuzzy environment. Int. J. Fuzzy Syst. Appl. (IJFSA) 2(4), 76–92 (2012)

    Article  Google Scholar 

  14. Kabir, G., Hasin, M.: Multiple criteria inventory classification using fuzzy analytic hierarchy process. Int. J. Ind. Eng. Comput. 3(2), 123–132 (2012)

    Google Scholar 

  15. Liu, J., Liao, X., Zhao, W., Yang, N.: A classification approach based on the outranking model for multiple criteria ABC analysis. Omega (2015)

    Google Scholar 

  16. Mareschal, B., Brans, J., Vincke, P., et al.: PROMETHEE: A new family of outranking methods in multicriteria analysis. ULB-Universite Libre de Bruxelles, Technical report (1984)

    Google Scholar 

  17. Mohammaditabar, D., Ghodsypour, S., O’Brien, C.: Inventory control system design by integrating inventory classification and policy selection. Int. J. Prod. Econ. 140(2), 655–659 (2012)

    Article  Google Scholar 

  18. Ng, W.L.: A simple classifier for multiple criteria ABC analysis. Eur. J. Oper. Res. 177(1), 344–353 (2007)

    Article  MATH  Google Scholar 

  19. Partovi, F., Burton, J.: Using the analytic hierarchy process for ABC analysis. Int. J. Oper. Prod. Manage. 13(9), 29–44 (1993)

    Article  Google Scholar 

  20. Partovi, F., Hopton, W.: The analytic hierarchy process as applied to two types of inventory problems. Prod. Inventory Manage. J. 35(1), 13 (1994)

    Google Scholar 

  21. Ramanathan, R.: ABC inventory classification with multiple-criteria using weighted linear optimization. Comput. Oper. Res. 33(3), 695–700 (2006)

    Article  MATH  Google Scholar 

  22. Roy, B.: ELECTRE III: Un algorithme de classement fondé sur une représentation floue des préférences en présence de critères multiples. Cahiers du CERO 20(1), 3–24 (1978)

    MATH  Google Scholar 

  23. Roy, B.: The outranking approach and the foundations of electre methods. Theory Decis. 31(1), 49–73 (1991)

    Article  MathSciNet  Google Scholar 

  24. Saaty, T.: The analytical hierarchy process: planning, setting priorities, resource allocation (1980)

    Google Scholar 

  25. Storn, R., Price, K.: Differential evolution-a simple and efficient adaptive scheme for global optimization over continuous spaces, vol. 3. ICSI, Berkeley (1995)

    MATH  Google Scholar 

  26. Storn, R., Price, K.: Differential evolution-a simple and efficient heuristic for global optimization over continuous spaces. J. Glob. Optim. 11(4), 341–359 (1997)

    Article  MathSciNet  MATH  Google Scholar 

  27. Tsai, C.Y., Yeh, S.W.: A multiple objective particle swarm optimization approach for inventory classification. Int. J. Prod. Econ. 114(2), 656–666 (2008)

    Article  Google Scholar 

  28. Zhou, P., Fan, L.: A note on multi-criteria ABC inventory classification using weighted linear optimization. Eur. J. Oper. Res. 182(3), 1488–1491 (2007)

    Article  MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Institut Supérieur de Gestion, Université de Tunis, Tunis, Tunisia

    Hedi Cherif

  2. Ecole Supérieure des Sciences Economiques et Commerciales de Tunis, Université de Tunis, Tunis, Tunisia

    Talel Ladhari

  3. College of Business, Umm Al-Qura University, Umm Al-Qura, Mecca, Saudi Arabia

    Talel Ladhari

Authors
  1. Hedi Cherif
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Talel Ladhari
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Hedi Cherif .

Editor information

Editors and Affiliations

  1. (MIR Labs), Machine Intelligence Research Labs, Auburn, Washington, USA

    Ajith Abraham

  2. Hassan 1st University, Settat, Morocco

    Abdelkrim Haqiq

  3. ENIS, University of Sfax, Sfax, Tunisia

    Adel M. Alimi

  4. Technopolis Rabat-Shore Rocade, International University of Rabat, Sala el Jadida, Morocco

    Ghita Mezzour

  5. Inst Applied Dept of Electronics, Taffala, University of Sousse, Sousse, Tunisia

    Nizar Rokbani

  6. Fakulti Teknologi Maklumat dan Komunikas, Universiti Teknikal Malaysia Melaka, Durian Tunggal, Malaysia

    Azah Kamilah Muda

Rights and permissions

Reprints and permissions

Copyright information

© 2017 Springer International Publishing AG

About this paper

Cite this paper

Cherif, H., Ladhari, T. (2017). Multiple Criteria Inventory Classification Approach Based on Differential Evolution and Electre III. In: Abraham, A., Haqiq, A., Alimi, A., Mezzour, G., Rokbani, N., Muda, A. (eds) Proceedings of the 16th International Conference on Hybrid Intelligent Systems (HIS 2016). HIS 2016. Advances in Intelligent Systems and Computing, vol 552. Springer, Cham. https://doi.org/10.1007/978-3-319-52941-7_8

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-52941-7_8

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-52940-0

  • Online ISBN: 978-3-319-52941-7

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation