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  4. Optimizing the trade-off between performance measures and operational risk in a food supply chain environment
 
research article

Optimizing the trade-off between performance measures and operational risk in a food supply chain environment

Voldrich, Simone
•
Wieser, Philippe  
•
Zufferey, Nicolas
March 1, 2020
Soft Computing

In the context of a growing world population and the need to use limited resources responsibly, this study is motivated by the increasing pressures on the food industry, which include issues of food security, safety, and waste. In the context of a global food supply chain, we combine processing time and cost (PT&C) with operational risk (ORk) in a novel integrated approach to designing and optimizing monitoring systems. This study of a flagship product widely consumed around the world provides quantitative analysis and results based on real-world data from an international food company. The findings indicate that our multi-objective methodology provides quantitative insights into-and is capable of quantifying-an unexpected nonlinear relationship between PT&C and ORk. We show numerically how to decrease PT&C significantly by means of a minor increase in ORk, an outcome which is highly appealing for the industry. In addition, we provide accurate measurements of the impact of each individual monitoring activity, which allows the identification of the monitoring activities that are most critical. Generalizable insights for practitioners are derived from a step-by-step optimization of the entire monitoring system.

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Type
research article
DOI
10.1007/s00500-019-04099-9
Web of Science ID

WOS:000518603800019

Author(s)
Voldrich, Simone
Wieser, Philippe  
Zufferey, Nicolas
Date Issued

2020-03-01

Publisher

SPRINGER

Published in
Soft Computing
Volume

24

Issue

5

Start page

3365

End page

3378

Subjects

Computer Science, Artificial Intelligence

•

Computer Science, Interdisciplinary Applications

•

Computer Science

•

supply chain management

•

manufacturing

•

quality management

•

risk management

•

monitoring-system

•

lead time

•

management

•

perspectives

•

framework

•

networks

•

models

Editorial or Peer reviewed

REVIEWED

Written at

EPFL

EPFL units
LEM-CDM  
Available on Infoscience
March 25, 2020
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/167629
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