Determining lot sizes and resource requirements: A review
Operations Research
Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Introduction to artificial neural systems
Introduction to artificial neural systems
Selection of vendors—a mixed-integer programming approach
CIE '96 Proceedings of the 19th international conference on Computers and industrial engineering
Industrial Applications of Fuzzy Control
Industrial Applications of Fuzzy Control
Foundations of Neuro-Fuzzy Systems
Foundations of Neuro-Fuzzy Systems
Neural Network Time Series Forecasting of Financial Markets
Neural Network Time Series Forecasting of Financial Markets
An intelligent system for customer targeting: a data mining approach
Decision Support Systems
Inventory lot-sizing with supplier selection
Computers and Operations Research
A hybrid genetic-neural architecture for stock indexes forecasting
Information Sciences: an International Journal - Special issue: Computational intelligence in economics and finance
The Fuzzy ART algorithm: A categorization method for supplier evaluation and selection
Expert Systems with Applications: An International Journal
Review article: A review of soft computing applications in supply chain management
Applied Soft Computing
Sustainable supplier selection: A ranking model based on fuzzy inference system
Applied Soft Computing
An intelligent supplier evaluation, selection and development system
Applied Soft Computing
Pig procurement plan considering pig growth and size distribution
Computers and Industrial Engineering
A fuzzy integral-based model for supplier evaluation and improvement
Information Sciences: an International Journal
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In supply chain management (SCM), multi-product and multi-period models are usually used to select the suppliers. In the real world of SCM, however, there are normally several echelons which need to be integrated into inventory management. This paper presents a hybrid intelligent algorithm, based on the push SCM, which uses a fuzzy neural network and a genetic algorithm to forecast the rate of demand, determine the material planning and select the optimal supplier. We test the proposed algorithm in a case study conducted in Iran.