Supplier Selection Based on a Neural Network Model Using Genetic Algorithm

In this paper, a decision-making model was developed to select suppliers using neural networks (NNs). This model used historical supplier performance data for selection of vendor suppliers. Input and output were designed in a unique manner for training purposes. The managers' judgments about suppliers were simulated by using a pairwise comparisons matrix for output estimation in the NN. To obtain the benefit of a search technique for model structure and training, genetic algorithm (GA) was applied for the initial weights and architecture of the network. The suppliers' database information (input) can be updated over time to change the suppliers' score estimation based on their performance. The case study illustrated shows how the model can be applied for suppliers' selection.

[1]  Gary W. Dickson,et al.  AN ANALYSIS OF VENDOR SELECTION SYSTEMS AND DECISIONS , 1966 .

[2]  W. Pedrycz,et al.  A fuzzy extension of Saaty's priority theory , 1983 .

[3]  K. Tan,et al.  Attitudes of US and European managers to supplier selection and assessment and implications for business performance , 2003 .

[4]  William Remus,et al.  Neural Network Models for Time Series Forecasts , 1996 .

[5]  Edward N. Timmerman.  An Approach to Vendor Performance Evaluation , 1986 .

[6]  Fong-Yuen Ding,et al.  Using data envelopment analysis to compare suppliers for supplier selection and performance improvement , 2000 .

[7]  Ching-Lai Hwang,et al.  Fuzzy Multiple Attribute Decision Making - Methods and Applications , 1992, Lecture Notes in Economics and Mathematical Systems.

[8]  John R. Current,et al.  Non-cooperative negotiation strategies for vendor selection , 1998, Eur. J. Oper. Res..

[9]  Jasmina Arifovic,et al.  Using genetic algorithms to select architecture of a feedforward artificial neural network , 2001 .

[10]  F. A. Lootsma,et al.  Multicriteria decision analysis with fuzzy pairwise comparisons , 1989 .

[11]  E. Mine Cinar,et al.  Neural Networks: A New Tool for Predicting Thrift Failures , 1992 .

[12]  Lakhmi C. Jain,et al.  Neural Network Training Using Genetic Algorithms , 1996 .

[13]  N.-E. Dahel.  Vendor selection and order quantity allocation in volume discount environments , 2003 .

[14]  T. Saaty,et al.  The Analytic Hierarchy Process , 1985 .

[15]  Peter M. Todd,et al.  Designing Neural Networks using Genetic Algorithms , 1989, ICGA.

[16]  Zhongsheng Hua,et al.  A modified fuzzy logarithmic least squares method for fuzzy analytic hierarchy process , 2006, Fuzzy Sets Syst..

[17]  Lawrence Davis,et al.  Training Feedforward Neural Networks Using Genetic Algorithms , 1989, IJCAI.

[18]  L. Ellram.  The Supplier Selection Decision in Strategic Partnerships , 1990 .

[19]  하성도,et al.  Supplier selection and management system considering relationships in supply chain management , 2001 .

[20]  Jonathan F. Bard,et al.  A COMPARISON OF THE ANALYTIC HIERARCHY PROCESS WITH MULTIATTRIBUTE UTILITY THEORY: A CASE STUDY , 1992 .

[21]  L. Darrell Whitley,et al.  Genetic algorithms and neural networks: optimizing connections and connectivity , 1990, Parallel Comput..

[22]  J. Seydel.  Supporting the paradigm shift in vendor selection: multicriteria methods for sole‐sourcing , 2005 .

[23]  W. C. Benton,et al.  Vendor selection criteria and methods , 1991 .

[24]  Ming S. Hung,et al.  A comparison of nonlinear optimization methods for supervised learning in multilayer feedforward neural networks , 1996 .

[25]  B. Curry,et al.  Neural networks: a need for caution , 1997 .

[26]  Wan Lung Ng,et al.  An efficient and simple model for multiple criteria supplier selection problem , 2008, Eur. J. Oper. Res..

[27]  Jinlong Zhang,et al.  A supplier-selecting system using a neural network , 1997, 1997 IEEE International Conference on Intelligent Processing Systems (Cat. No.97TH8335).

[28]  Jatinder N. D. Gupta,et al.  Comparative evaluation of genetic algorithm and backpropagation for training neural networks , 2000, Inf. Sci..

[29]  Robert E. Dorsey,et al.  Genetic algorithms for estimation problems with multiple optima , 1995 .

[30]  Thomas O. Boucher,et al.  Strong transitivity, rationality and weak monotonicity in fuzzy pairwise comparisons , 1998, Fuzzy Sets Syst..

[31]  Khurrum S. Bhutta,et al.  Supplier selection problem: a comparison of the total cost of ownership and analytic hierarchy process approaches , 2002 .

[32]  Jeffrey S. Racine,et al.  Semiparametric ARX neural-network models with an application to forecasting inflation , 2001, IEEE Trans. Neural Networks.

[33]  J. Current,et al.  An optimization approach to determining the number of vendors to employ , 2000 .

[34]  Thomas O. Boucher,et al.  A consistency test for rational weights in multi-criterion decision analysis with fuzzy pairwise comparisons , 1997, Fuzzy Sets Syst..

[35]  Wolfgang Hauke.  Fuzzy Multiple Attribute Decision Making (Fuzzy-MADM) , 1998 .

[36]  Randall S. Sexton,et al.  Toward global optimization of neural networks: A comparison of the genetic algorithm and backpropagation , 1998, Decis. Support Syst..

[37]  C. Weber.  A data envelopment analysis approach to measuring vendor performance , 1996 .