Abstract
Supplier selection decisions are typically multi-objectives in nature and it is an important component of production and logistics management for many firms. The present study mainly investigate a multi-objective supplier selection planing problem in fuzzy environment and the uncertain model is converted into deterministic form by the expected value measure (EVM). This paper aims at multi-objective optimization for minimizing cost and maximizing product quality level. For solving the multi-objective problem a weighted sum base genetic algorithm is applied and the best solution is provided using fuzzy simulation. Finally, a numerical example is used to illustrate the effectiveness of the proposed model and solution approach.
Keywords
- Multiobjective model
- Supplier selection
- Supply chain
- Fuzzy simulation
- Genetic algorithm
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Acknowledgments
The authors wish to thank the anonymous referees for their helpful and constructive comments and suggestions. The work is supported by the National Natural Science Foundation of China (No. 71301109), the Western and Frontier Region Project of Humanity and Social Sciences Research, Ministry of Education of China (No. 13XJC630018), the Philosophy and Social Sciences Planning Project of Sichuan province (NO. SC12BJ05), and the Initial Funding for Young Teachers of Sichuan University (No. 2013SCU11014).
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Hashim, M., Yao, L., Nadeem, A.H., Nazim, M., Nazam, M. (2014). Multi-objective Optimization Model for Supplier Selection Problem in Fuzzy Environment. In: Xu, J., Cruz-Machado, V., Lev, B., Nickel, S. (eds) Proceedings of the Eighth International Conference on Management Science and Engineering Management. Advances in Intelligent Systems and Computing, vol 281. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-55122-2_104
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DOI: https://doi.org/10.1007/978-3-642-55122-2_104
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