Combined forecasting and cognitive Decision Support System for Indian green coffee supply chain predictive analytics

2015 ◽  
Author(s):  
N. Ayyanathan ◽  
A. Kannammal
Keyword(s):  
Supply Chain ◽  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Predictive Analytics ◽  
Green Coffee ◽  
Cognitive Decision ◽  
Combined Forecasting

A reliable decision support system for fresh food supply chain management

2017 ◽  
Vol 56 (4) ◽  
pp. 1458-1485 ◽  
Author(s):  
Gabriella Dellino ◽  
Teresa Laudadio ◽  
Renato Mari ◽  
Nicola Mastronardi ◽  
Carlo Meloni
Keyword(s):  
Supply Chain ◽  
Decision Support ◽  
Supply Chain Management ◽  
Decision Support System ◽  
Support System ◽  
Food Supply ◽  
Food Supply Chain ◽  
Chain Management ◽  
Fresh Food

scholarly journals A hybrid decision support system for analyzing challenges of the agricultural supply chain

2019 ◽  
Vol 18 ◽  
pp. 19-32 ◽  
Author(s):  
Bhaskar B. Gardas ◽  
Rakesh D. Raut ◽  
Naoufel Cheikhrouhou ◽  
Balkrishna E. Narkhede
Keyword(s):  
Supply Chain ◽  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Agricultural Supply

Decision Support System for Real Time Vehicle Routing in Indian Dairy Industry: A Case Study

2013 ◽  
Vol 6 (4) ◽  
pp. 77-101 ◽  
Author(s):  
R. A. Malairajan ◽  
K. Ganesh ◽  
M. Punnniyamoorthy ◽  
S. P. Anbuudayasankar
Keyword(s):  
Supply Chain ◽  
Decision Support ◽  
Supply Chain Management ◽  
Decision Support System ◽  
Vehicle Routing ◽  
Support System ◽  
Distribution System ◽  
Physical Distribution ◽  
Chain Management ◽  
Distribution Logistics

In today’s highly competitive and demanding environment, the pressure on both public and private organizations is to achieve a better way to deliver values to end customers. There has been a growing recognition that the two goals, cost reduction and customer service are achieved through Logistics and Supply Chain Management (SCM). Transportation of goods continues an important part of in-bound as well as outbound logistics of Supply Chain Management (SCM). Efficient distribution of goods and services is of great importance in today’s competitive market, because transportation constitutes a considerable portion of the purchase price of most products or services. Vehicle routing is considered as an important resource in a distribution logistics management system. Effective plan and control of vehicle operation can significantly reduce the cost of physical distribution system. To overcome the challenges of changing environment, the scheme of vehicle control of a physical distribution system should be dynamic. Thus India has become the top milk producing country in the world. This study addresses the vehicle routing aspect of distribution logistics in Sangam dairy supply chain of Guntur district in Andhra Pradesh. The problem is viewed as Vehicle Routing Problem with Backhauls (VRPB) and a mathematical model is developed with the consideration of various practical constraints. Moreover, a decision support system is developed for dynamic VRPB, which would help the manager in making operational and tactical decisions.

scholarly journals Weighted Deep Neural Network Based Clinical Decision Support System for the Determination of Fetal Health

2019 ◽  
Vol 8 (4) ◽  
pp. 8564-8569
Keyword(s):  
Neural Network ◽  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Deep Neural Network ◽  
Predictive Analytics ◽  
Clinical Decision ◽  
Svm Classifier ◽  
Healthcare Data ◽  
The Individual

Healthcare industry is undergoing changes at a tremendous rate due to healthcare innovations. Predictive analytics is increasingly being used to diagnose the patient’s ailments and provide actionable insights into already existing healthcare data. The paper looks at a decision support system for determining the health status of the foetus from cardiotographic data using deep learning neural networks. The foetal health records are classified as normal, suspect and pathological. As the multiclass cardiotographic datset of the foetus shows a high degree of imbalance a weighted deep neural network is applied. To overcome the accuracy paradox due to the multiclass imbalance, relevant metrics such as the sensitivity, specificity, F1 Score and Gmean are used to measure the performance of the classifier rather than accuracy. The metrics are applied to the individual classes to ensure that the positive cases are identified correctly. The weighted DNN based classifier is able to classify the positive instances with Gmean score of 91% which is better than than the SVM classifier.

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