Addressing the scheduling of chemical supply chains under demand uncertainty

Guillén, Gonzalo; Espuña, Antonio; Puigjaner, Luís

doi:10.1002/aic.10973

Cited by 14 publications

(5 citation statements)

References 40 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…√ √ Chen and Lee √ √ √ Fandel and Stammen √ Gjerdrum et al √ Guillén and co-workers ,,, √ √ √ √ Gupta and Maranas √ Gupta et al √ Hugo and Pistikopoulos 15 √ √ Iyer and Grossmann √ Jun-Hyung et al …”

Section: Integrating Process Operations and Financesmentioning

confidence: 99%

Enhancing Corporate Value in the Optimal Design of Chemical Supply Chains

Laínez

Guillén‐Gosálbez

Badell

et al. 2007

Ind. Eng. Chem. Res.

Self Cite

View full text Add to dashboard Cite

The tight profit margins under which chemical process industries (CPI) operate are forcing companies to pay more and more attention to the design and operation of their supply chains (SCs). Traditional approaches available in the process systems engineering (PSE) literature to address the design and operation of chemical SCs usually focus on the process operations side and neglect the financial part of the problem. This work deals with the design and retrofit of chemical SCs and proposes a novel framework to address this problem that consists of incorporating financial considerations at the strategic decision-making level. Within this framework, the decisions that have a long-lasting effect on the firm are assessed through integrated models that are capable of holistically optimizing the combined effects of process operations and finances. The proposed approach adopts the corporate value of the firm (CV) as the objective to be maximized. The main advantages of such a holistic approach are highlighted through a case study, in which a comparison with the traditional biased method that pursues a fairly simple performance indicator as objective and disregards the financial variables and constraints of the problem is carried out. The integrated solution guarantees the feasibility of the strategic decisions from the financial point of view by ensuring liquidity control. Furthermore, it also leads to a superior economic performance as it exhibits a greater capacity of improving the value of the firm.

show abstract

Section: Integrating Process Operations and Financesmentioning

confidence: 99%

Enhancing Corporate Value in the Optimal Design of Chemical Supply Chains

Laínez

Guillén‐Gosálbez

Badell

et al. 2007

Ind. Eng. Chem. Res.

Self Cite

View full text Add to dashboard Cite

show abstract

“…This paradigm shift in the scope of the analysis carried out in PSE has led to the development of a new generation of tools that provide decision‐support for SCM 1–7. These strategies enable the coordination and simultaneous optimization of manufacturing sites, logistics, and distribution tasks in a SC environment.…”

Section: Introductionmentioning

confidence: 99%

Optimal design and planning of sustainable chemical supply chains under uncertainty

2008

View full text Add to dashboard Cite

This article addresses the design of sustainable chemical supply chains in the presence of uncertainty in the life cycle inventory associated with the network operation. The design task is mathematically formulated as a bi-criterion stochastic mixed-integer nonlinear program (MINLP) that simultaneously accounts for the maximization of the net present value and the minimization of the environmental impact for a given probability level. The environmental performance is measured through the Eco-indicator 99, which incorporates the recent advances made in Life Cycle Assessment. The stochastic model is converted into its deterministic equivalent by reformulating the probabilistic constraint required to calculate the environmental impact in the space of uncertain parameters. The resulting deterministic bi-criterion MINLP problem is further reformulated as a parametric MINLP, which is solved by decomposing it into two sub-problems and iterating between them. The capabilities of the proposed model and solution procedure are illustrated through two case studies for which the set of Pareto optimal, or efficient solutions that trade-off environmental impact and profit, are calculated. These solutions provide valuable insights into the design problem and are intended to guide the decision maker towards the adoption of more sustainable design alternatives.

show abstract

“…A review paper for optimization under uncertainty has been published. 8 Recent research in this area can be divided into various categories: simulation-based optimization, 9 scenariobased optimization, 7 chance-constrained programming, 10 multistage stochastic programming with recourse, 11 approximate dynamic programming, 12 multiparametric programming, 13 genetic algorithm with mathematical programming, 14 robust optimization with bounded uncertainty, 15 a fuzzy optimization model, 16 and a branch and cut algorithm that uses Lagrangean decomposition. 17 However, the models developed to date are unsuitable for use in real applications due to severe computational complexity arising from the treatment of uncertainty as well as unknown probabilistic parameters.…”

Section: Introductionmentioning

confidence: 99%

Optimal design of batch‐storage network under joint uncertainties

Yi¹

2008

AIChE Journal

View full text Add to dashboard Cite

This study sought to find analytic solutions to the problem of determining the optimal capacity of a batch-storage network to meet demand for finished products in a system undergoing joint random variations of operating time and batch quantity. The raw material purchasing flow and final product demand flow are susceptible to joint random variations in the order cycle time and batch size. The production processes also have joint random variations in production cycle time and product quantity. Waste regeneration or disposal processes are included into the network to treat the spoiled materials from failed batches. The objective function of the optimization is minimizing the expected total cost, which is composed of setup and inventory holding costs as well as the capital costs of constructing processes and storage units. A production and inventory method, the PSW (periodic square wave) model, provides a unique graphical method to find the upper/lower bounds and average of random flows, which are used to construct terms of the objective function and constraints of the optimization model. The advantage of this model is that it provides a set of simple analytic solutions while also maintaining a realistic description of the random material flows between processes and storage units; as a consequence of these analytic solutions, the computation burden is significantly reduced. The proposed method has the potential to rapidly provide very useful data on base investment decisions during the early plant design stage. It should be particularly useful when these decisions must be made in a highly uncertain business environment.

show abstract

Addressing the scheduling of chemical supply chains under demand uncertainty

Cited by 14 publications

References 40 publications

Enhancing Corporate Value in the Optimal Design of Chemical Supply Chains

Enhancing Corporate Value in the Optimal Design of Chemical Supply Chains

Optimal design and planning of sustainable chemical supply chains under uncertainty

Optimal design of batch‐storage network under joint uncertainties

Contact Info

Product

Resources

About