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A SP approach for decision-dependent uncertainty in production planning under non-compliance risk
Alwin Haensel

05 October 2012, 10h30 - 05 October 2012, 11h30
Salle/Bat : 475/PCRI-N
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Résumé :
Governmental regulation pressure on production quality and standards is increasing in many areas, especially in the chemical, food and pharmaceutical industries. Therefore, a production plan needs to consider the risks of failing the quality inspection by the authority agency. Inspection realizations are clearly dependent on the previous production planning decisions. Normally stochastic programs assume the random process to be independent of the optimization decision. This dependency increases the complexity of the underlying problem significantly. The uncertain inspection realizations are modelled by scenarios, which are generated according given product-site hazards. We propose a general scenario based stochastic programming approach and start initially with a risk-neutral model maximizing the expected revenue. The model is extended to account for more risk-averse attitudes of the decision maker by introducing probabilistic constraints. The main focus is on a direct CVaR (conditional value-at-risk) optimization formulation.

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