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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Paperback. Etat : Very Good. 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 7¾" - 9¾" tall. N° de réf. du vendeur ec506
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Kartoniert / Broschiert. Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Khor Cheng SeongCheng Seong Khor is a lecturer-cum-researcher at the PETRONASnUniversity of Technology. His research interests involves thenapplication of systemsnengineering and optimization to chemical process systemsnengineering (. N° de réf. du vendeur 5388179
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Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This work proposes a hybrid of stochastic programming(SP) approaches for an optimal midterm refineryplanning that addresses three forms of uncertainties:prices of crude oil and products, demands, andyields. An SP technique that utilizes compensatingslack variables is employed to explicitly account forconstraint violations to increase model tractability.Four approaches are considered to achieve solutionand model robustness: (1) the Markowitz'smean-variance (MV) model to handle randomness in theobjective coefficients by minimizing the variance(economic risk) of the expected value of the randomcoefficients; (2) the two-stage SP with fixedrecourse to deal with randomness in the RHS and LHScoefficients of the constraints by minimizing theexpected recourse costs; (3) incorporation of the MVmodel within the framework in (2) to formulate amean risk model that minimizes the expectation andthe operational risk measure of variance of therecourse costs; and (4) reformulation of the model in(3) by adopting mean-absolute deviation (MAD) as theoperational risk measure imposed by the recoursecosts for a novel refinery planning application. Anumerical example is illustrated. N° de réf. du vendeur 9783836477925
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