CX3 - A paperback book in very good condition that has some bumped corners, light discoloration and shelf wear. A Hybrid of Stochastic Programming Approaches with Economic and Operational Risk Management. 9"x6", 288 pages. Satisfaction Guaranteed. This work proposes a hybrid of stochastic programming (SP) approaches for an optimal midterm refinery planning that addresses three forms of uncertainties: prices of crude oil and products, demands, and yields. An SP technique that utilizes compensating slack variables is employed to explicitly account for constraint violations to increase model tractability. Four approaches are considered to achieve solution and model robustness: (1) the Markowitz's mean-variance (MV) model to handle randomness in the objective coefficients by minimizing the variance (economic risk) of the expected value of the random coefficients; (2) the two-stage SP with fixed recourse to deal with randomness in the RHS and LHS coefficients of the constraints by minimizing the expected recourse costs; (3) incorporation of the MV model within the framework in (2) to formulate a mean?risk model that minimizes the expectation and the operational risk measure of variance of the recourse costs; and (4) reformulation of the model in (3) by adopting mean-absolute deviation (MAD) as the operational risk measure imposed by the recourse costs for a novel refinery planning application. A numerical example is illustrated. Size: 8vo - over 7�" - 9�" tall.

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Bibliographic Details

Title

Optimization Strategies: Petroleum Refinery Planning Under Uncertainty

Publisher

VDM Verlag Dr. M�ller

Publication Date

2008

Language

English

ISBN 10

3836477920

ISBN 13

9783836477925

Binding

Paperback

Condition

Very Good

Dust Jacket Condition

No Jacket as Issued

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Synopsis

This work proposes a hybrid of stochastic programming (SP) approaches for an optimal midterm refinery planning that addresses three forms of uncertainties: prices of crude oil and products, demands, and yields. An SP technique that utilizes compensating slack variables is employed to explicitly account for constraint violations to increase model tractability. Four approaches are considered to achieve solution and model robustness: (1) the Markowitz's mean-variance (MV) model to handle randomness in the objective coefficients by minimizing the variance (economic risk) of the expected value of the random coefficients; (2) the two-stage SP with fixed recourse to deal with randomness in the RHS and LHS coefficients of the constraints by minimizing the expected recourse costs; (3) incorporation of the MV model within the framework in (2) to formulate a mean?risk model that minimizes the expectation and the operational risk measure of variance of the recourse costs; and (4) reformulation of the model in (3) by adopting mean-absolute deviation (MAD) as the operational risk measure imposed by the recourse costs for a novel refinery planning application. A numerical example is illustrated.

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