Abstract
In times of economic crises and increasing market competition, business stability, quality, safety and supply chain flexibility and cost optimization play an increasing role in companies that strive to stay and survive in the market. A wise choice of suppliers, in such circumstances, becomes increasingly important prerequisite for the success of any company. This paper presents a novel model for supplier assessment. The proposed model considers the performance of suppliers classified into several different groups of questions related to all the relevant issues: finance, logistics, competitiveness, quality and level of supplier services. This model can be applied in a variety of companies and for different supplier categories based on their purchase categories and therefore achieve a realistic assessment.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Abraham, A.: Hybrid Soft Computing and Applications. International Journal of Computational Intelligence and Applications 8(1), 1–2 (2009)
Burke, G.J., Carrillo, J.E., Vakharia, A.J.: Single versus multiple supplier sourcing strategies. European Journal of Operational Research 182(1), 95–112 (2007)
Corchado, E., Arroyo, A., Tricio, V.: Soft computing models to identify typical meteorological days. Logic Journal of the IGPL 19(2), 373–383 (2011)
Huang, C.F.: A hybrid stock selection model using genetic algorithms and support vector regression. Applied Soft Computing 12(2), 807–818 (2012)
Kumar, M., Vrat, P., Shankar, R.: A fuzzy goal programming approach for vendor selection problem in a supply chain. Computers and Industrial Engineering 46(1), 69–85 (2004)
Ho, W., Xu, X., Dey, P.K.: Multi-criteria decision making approaches for supplier evaluation and selection: a literature review. European Journal of Operational Research 202(1), 16–24 (2010)
Mosleh, M., Otadi, M.: Simulation and evaluation of fuzzy differential equations by fuzzy neural network. Applied Soft Computing (2012), doi:10.1016/j.asoc.2012.03.041
Porter, M.: Competitive Advantage, pp. 38–40. The Free Press, New York (1985)
Sedano, J., Curiel, L., Corchado, E., Cal, E., Villar, J.R.: A soft computing method for detecting lifetime building thermal insulation failures. Integrated Computer-Aided Engineering 17(2), 103–115 (2012)
Simić, D., Simić, S.: A Review: Approach of Fuzzy Models Applications in Logistics. In: Burduk, R., Kurzyński, M., Woźniak, M., Żołnierek, A. (eds.) CORES 2011. AISC, vol. 95, pp. 717–726. Springer, Heidelberg (2011)
Szczepanik, M., Poteralski, A., Ptaszny, J., Burczyński, T.: Hybrid Particle Swarm Optimizer and Its Application in Identification of Room Acoustic Properties. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds.) EC 2012 and SIDE 2012. LNCS (LNAI), vol. 7269, pp. 386–394. Springer, Heidelberg (2012)
Talluri, S., Baker, R.C.: A multi-phase mathematical programming approach for effective supply chain design. European Journal of Operational Research 141(3), 544–558 (2002)
Talluri, S., Narasimhan, R.: Vendor evaluation with performance variability: A max-min approach. European Journal of Operational Research 146(3), 543–552 (2003)
Wang, T.Y., Yang, Y.H.: A fuzzy model for supplier selection in quantity discount environments. Expert Systems with Applications 36(10), 12179–12187 (2009)
Weber, C.A., Current, J.R., Benton, W.C.: Vendor selection criteria and methods. European Journal of Operational Research 50(1), 2–18 (1991)
Zadeh, L.: Soft computing and fuzzy logic. Computer Journal of IEEE Software 11(6), 48–56 (1994)
Zhao, S.Z., Iruthayarajan, M.W., Baskar, S., Suganthan, P.N.: Multi-objective robust PID controller tuning using two lbests multi-objective particle swarm optimization. Information Sciences 181(16), 3323–3335 (2011)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Simić, D., Svirčević, V., Simić, S. (2013). An Approach of Genetic Algorithm to Model Supplier Assessment in Inbound Logistics. In: Snášel, V., Abraham, A., Corchado, E. (eds) Soft Computing Models in Industrial and Environmental Applications. Advances in Intelligent Systems and Computing, vol 188. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32922-7_9
Download citation
DOI: https://doi.org/10.1007/978-3-642-32922-7_9
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-32921-0
Online ISBN: 978-3-642-32922-7
eBook Packages: EngineeringEngineering (R0)