Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Group decision support with the analytic hierarchy process
Decision Support Systems
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Supplier selection and order lot sizing modeling: A review
Computers and Operations Research
Computers and Industrial Engineering
Supply chain optimisation using evolutionary algorithms
International Journal of Computer Applications in Technology
A new hybrid model for the supplier selection decision
International Journal of Business Information Systems
Expert Systems with Applications: An International Journal
BestChoice: a decision support system for supplier selection in e-marketplaces
DEECS'06 Proceedings of the Second international conference on Data Engineering Issues in E-Commerce and Services
A hybrid MCDM model for strategic vendor selection
Mathematical and Computer Modelling: An International Journal
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The paper presents a simulation-optimization approach using genetic algorithm to the supplier selection problem. The problem consists in selecting a portfolio of suppliers from a set of pre-selected candidates. The supplier selection is a multi-criteria problem that includes both qualitative and quantitative criteria. In order to select the best suppliers it is crucial to make a trade off between these tangible and intangible criteria, some of which may be contradictory. The proposed approach uses discrete-event simulation for performance evaluation of a supplier portfolio and a genetic algorithm for optimum portfolio identification based on performance indices estimated by the simulation. Numerical results on a real-life case study are presented.