Iftekhar A Karimi, Rajagopalan Srinivasan's 11th International Symposium on Process Systems Engineering PDF

By Iftekhar A Karimi, Rajagopalan Srinivasan

ISBN-10: 0444595058

ISBN-13: 9780444595058

ISBN-10: 0444595066

ISBN-13: 9780444595065

ISBN-10: 0444595074

ISBN-13: 9780444595072

Vol. 1. half A -- v. 2. half B

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Extra info for 11th International Symposium on Process Systems Engineering

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Part A includes the plenary, keynote, short oral, and poster contributions, while Part B comprises the full oral presentations. We are indebted to many from the PSE community, who contributed their invaluable time and effort as members of the three main committees of PSE2012, namely the International Program Committee (IPC), the Local Organizing Committee (LOC), and the Graduate Organizing Committee (GOC). The LOC reviewed nearly 580 initial abstracts and also full-length papers. The IPC members provided at least two timely and critical reviews for each contributed full-length paper.

Stochastic imbalance is not known in advance and only becomes known after it is too late to adjust component supply. This kind of imbalance can be caused by an incorrect demand forecast, an unexpected last-minute supply disruption, or incorrect planning. Deterministic and stochastic imbalances in the supply chain not only have separate causes, but also require different solution approaches. Since a deterministic imbalance is known within the lead-time of most components, the demand can be shaped into other products and the supply can be adjusted accordingly.

The resulting customer choice model depicts latent inter-product relationships, and is combined with up-to-date product-level forecasts to give a full picture of demand. Product demand forecasts and customer choice modeling are integrated into a two-stage decision process for customer purchases. The first stage occurs prior to demand shaping and involves determination of an unshaped product choice for each customer. Our assumption is that the distribution of unshaped product choices is, with the exception of some random forecast error, represented accurately by product demand forecasts that are generated through the traditional planning process.

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11th International Symposium on Process Systems Engineering by Iftekhar A Karimi, Rajagopalan Srinivasan

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