Learning internal representations by error propagation
Parallel distributed processing: explorations in the microstructure of cognition, vol. 1
Neural networks: algorithms, applications, and programming techniques
Neural networks: algorithms, applications, and programming techniques
Expert systems applications in engineering and manufacturing
Expert systems applications in engineering and manufacturing
Information distortion in a supply chain: the bullwhip effect
Management Science - Special issue on frontier research in manufacturing and logistics
Introduction to Artificial Neural Systems
Introduction to Artificial Neural Systems
Unresolved Issues in Supply Chain Network Design
Information Systems Frontiers
A strategic model for supply chain design with logical constraints: formulation and solution
Computers and Operations Research
Computer-assisted supply chain configuration based on supply chain operations reference (SCOR) model
Computers and Industrial Engineering
Neural Networks: A Comprehensive Foundation (3rd Edition)
Neural Networks: A Comprehensive Foundation (3rd Edition)
Optimizing the Supply Chain Configuration for New Products
Management Science
A multi-echelon inventory management framework for stochastic and fuzzy supply chains
Expert Systems with Applications: An International Journal
A steady-state genetic algorithm for multi-product supply chain network design
Computers and Industrial Engineering
Neuro-fuzzy rule generation: survey in soft computing framework
IEEE Transactions on Neural Networks
Model selection with considering the CO2 emission alone the global supply chain
Journal of Intelligent Manufacturing
Review Article: Applications of neuro fuzzy systems: A brief review and future outline
Applied Soft Computing
| Hi-index | 12.05 |
In this study, an integrated supply chain (SC) design model is developed and a SC network design case is examined for a reputable multinational company in alcohol free beverage sector. Here, a three echelon SC network is considered under demand uncertainty and the proposed integrated neuro-fuzzy and mixed integer linear programming (MILP) approach is applied to this network to realize the design effectively. Matlab 7.0 is used for neuro-fuzzy demand forecasting and, the MILP model is solved using Lingo 10.0. Then Matlab 7.0 is used for artificial neural network (ANN) simulation to supply a comparative study and to show the applicability and efficiency of ANN simulation for this type of problem. By evaluating the output data, the SC network for this case is designed, and the optimal product flow between the factories, warehouses and distributors are calculated. Also it is proved that the ANN simulation can be used instead of analytical computations because of ensuring a simplified representation for this method and time saving.