Mathematical programming approaches to the synthesis of chemical process systems

Grossmann, Ignacio E.; Caballero, José A.; Yeomans, Hector

doi:10.1007/bf02698263

Cited by 168 publications

(136 citation statements)

References 193 publications

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“…Ciric & Floudas, 1990;Hostrup, Gani, Kravanja, Sorsak, & Grossmann, 2001;Papalexandri & Pistikopoulos, 1996). A recent review of these methods has been published by Grossmann, Caballero, and Yeomans (1999) and their applicability, limitations and potentials are discussed by Grossmann and Daichendt (1996), Gruhn and Noronha (1998), and Kallrath (2000).…”

Section: Integer Non-linear Optimizationmentioning

confidence: 99%

Multi-objective process design in multi-purpose batch plants using a Tabu Search optimization algorithm

Cavin

Fischer

Glover

et al. 2004

Computers & Chemical Engineering

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Chemical batch processes are typically used for the production of speciality chemicals and pharmaceuticals. Due to the still growing importance of this type of processing, design methods are required that take into account the special requirements and constraints in the corresponding production facilities. We developed a method that optimizes the design of a single chemical process to be implemented in an existing multi-purpose batch plant, in which a well-defined set of equipment units is available for realizing this process. In the optimization, three objectives with different priorities are considered. A flexible metaheuristic algorithm, Tabu Search (TS), has been implemented to solve this multi-objective combinatorial non-linear problem. We started from a basic form of TS to determine the effectiveness of this version as well as establish the relative strengths and weaknesses of first level TS strategies. Our investigation includes a thorough examination of algorithm parameters and of implementation issues to identify algorithm settings that can handle the whole class of problems considered. Overall, we concluded that the basic form of TS-using fixed default settings-exhibits highly attractive performance features for solving the problems at hand. Moreover, comparison with a multi-start steepest descent algorithm shows that a basic TS approach conducts a global search more effectively. As illustrated by three case studies, the new method is well suited for identifying optimal designs of a chemical process to be implemented in an existing multi-purpose batch plant. The approach is particularly suited for considering multiple prioritized objectives and for enabling the use of external (e.g. commercial) batch process simulation software as a black-box model for the process evaluations.

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Section: Integer Non-linear Optimizationmentioning

confidence: 99%

Multi-objective process design in multi-purpose batch plants using a Tabu Search optimization algorithm

Cavin

Fischer

Glover

et al. 2004

Computers & Chemical Engineering

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“…If, in addition, plants operate in discrete modes or connections between various units, e.g., tanks and crackers or vacuum columns have to be chosen selectively, then mixed-integer nonlinear optimization problems need to be solved. Process network flow or process synthesis problems [30] usually fall into this category, too. Examples are heat exchanger or mass exchange networks.…”

Section: Special Features In the Process Industrymentioning

confidence: 99%

“…A product requirement which has to be satisfied is not prescribed. Instead, market prices C p (P up ) in units of $/kg for raw material P 0 and end products P 71 , P 72 , P 73 , P 74 , P 75 are given as [5,10,10,30,20,15].…”

Section: Taskmentioning

confidence: 99%

Planning and scheduling in the process industry

Kallrath¹

2002

OR Spectrum

311

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Since there has been tremendous progress in planning and scheduling in the process industry during the last 20 years, it might be worthwhile to give an overview of the current state-of-the-art of planning and scheduling problems in the chemical process industry. This is the purpose of the current review which has the following structure: we start with some conceptional thoughts and some comments on special features of planning and scheduling problems in the process industry. In Section 2 the focus is on planning problems while in Section 3 different types of scheduling problems are discussed. Section 4 presents some solution approaches especially those applied to a benchmark problem which has received considerable interest during the last years. Section 5 allows a short view into the future of planning and scheduling. In the appendix we describe the WestenbergerKallrath problem which has already been used extensively as a benchmark problem for planning and scheduling in the process industry.

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“…However, depending on the data specified and the final objective of the model user four types of different problems are considered [1,2]:…”

Section: Introductionmentioning

confidence: 99%

“…Therefore, the design and optimization is usually performed in an equation based environment (all equations solved simultaneously) using general modeling systems or field specific modeling systems [7]. In the case of synthesis, the model takes the form of a Mixed-integer (Non)Linear Programming problem [2,8,9] (MINLP) where discrete decisions are related to integer (binary) variables or a Generalized Disjunctive Programming Problem (GDP) [10] Developments in the design, optimization and synthesis of chemical processes over the last years have been impressive at all levels: from individual unit operations, to subsystems, and even to complete flowsheet optimization (see for instance the following books [8,[11][12][13][14]). …”

Section: Introductionmentioning

confidence: 99%

Integration of different models in the design of chemical processes: Application to the design of a power plant

2014

Self Cite

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With advances in the synthesis and design of chemical processes there is an increasing need for more complex mathematical models with which to screen the alternatives that constitute accurate and reliable process models. Despite the wide availability of sophisticated tools for simulation, optimization and synthesis of chemical processes, the user is frequently interested in using the 'best available model'. However, in practice, these models are usually little more than a black box with a rigid input-output structure. In this paper we propose to tackle all these models using generalized disjunctive programming to capture the numerical characteristics of each model (in equation form, modular, noisy, etc.) and to deal with each of them according to their individual characteristics. The result is a hybrid modular -equation based approach that allows synthesizing complex processes using different models in a robust and reliable way. The capabilities of the proposed approach are discussed with a case study: the design of a utility system power plant that has been decomposed into its constitutive elements, each treated differently numerically. And finally, numerical results and conclusions are presented.

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Mathematical programming approaches to the synthesis of chemical process systems

Cited by 168 publications

References 193 publications

Multi-objective process design in multi-purpose batch plants using a Tabu Search optimization algorithm

Multi-objective process design in multi-purpose batch plants using a Tabu Search optimization algorithm

Planning and scheduling in the process industry

Integration of different models in the design of chemical processes: Application to the design of a power plant

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