Optimal periodic scheduling of multipurpose batch plants

Shah, Nilay; Pantelides, Constantinos C.; Sargent, R. W. H.

doi:10.1007/bf02023176

Cited by 88 publications

(71 citation statements)

References 12 publications

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“…The simplest one is when cyclic schedules with infinite horizon are considered [245][246][247][248][249]. In this case, the objective function is divided by the length of the cycle time, yielding a linear fractional objective function.…”

Section: Planning and Schedulingmentioning

confidence: 99%

Review of Mixed‐Integer Nonlinear and Generalized Disjunctive Programming Methods

Trespalacios

Grossmann

2014

Chemie Ingenieur Technik

150

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This work presents a review of the applications of mixed-integer nonlinear programming (MINLP) in process systems engineering (PSE). A review on the main deterministic MINLP solution methods is presented, including an overview of the main MINLP solvers. Generalized disjunctive programming (GDP) is an alternative higher-level representation of MINLP problems. This work reviews some methods for solving GDP models, and techniques for improving MINLP methods through GDP. The paper also provides a high-level review of the applications of MINLP in PSE, particularly in process synthesis, planning and scheduling, process control and molecular computing.

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Section: Planning and Schedulingmentioning

confidence: 99%

Review of Mixed‐Integer Nonlinear and Generalized Disjunctive Programming Methods

Trespalacios

Grossmann

2014

Chemie Ingenieur Technik

150

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“…Nevertheless, there are numerous promising contributions (see, for instance, [67], [45], [55], [4], [65], [63], [52], [69]) for problems in the process industry. What makes scheduling problems so difficult?…”

Section: Solution Approaches Used In Schedulingmentioning

confidence: 99%

Planning and scheduling in the process industry

Kallrath¹

2002

OR Spectrum

308

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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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“…Nevertheless, there are numerous promising contributions 51,50,36,50,46,4 , especially from researchers in the chemical engineering community. What makes scheduling problems so dif®cult?…”

Section: Solving Scheduling Problems Effectivelymentioning

confidence: 99%

Mixed Integer Optimization in the Chemical Process Industry

Kallrath¹

2000

Chemical Engineering Research and Design

112

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Proper organization, planning and design of production, storage locations, transportation and scheduling are vital to retain the competitive edge of companies in the global economy. Typical additional problems in the chemical industry suitable for optimization are process design, process synthesis and multi-component blended-¯ow problems leading to nonlinear or even mixed integer nonlinear models. Mixed integer optimization (MIP) determines optimal solutions of such complex problems; the development of new algorithms, software and hardware allow the solution of larger problems in acceptable times.This tutorial paper addresses two groups. The focus towards the ®rst group (managers and senior executives) and readers who are not very familiar with mathematical programming is to create some awareness regarding the potential bene®ts of MIP, to transmit a sense of what kind of problems can be tackled, and to increase the acceptance of MIP. The second group (a more technical audience with some background in mathematical optimization), might rather appreciate the state-of-the-art view on good-modelling practice, algorithms and an outlook into global optimization.Some real-world MIP problems solved by BASF's mathematical consultants are brie¯y described, among them discrete blending and multi-stage production planning and distribution with several sites, products and periods. Finally, there is a focus on future perspectives and sources of MIP support are indicated from academia, software providers and consulting ®rms.

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Optimal periodic scheduling of multipurpose batch plants

Cited by 88 publications

References 12 publications

Review of Mixed‐Integer Nonlinear and Generalized Disjunctive Programming Methods

Review of Mixed‐Integer Nonlinear and Generalized Disjunctive Programming Methods

Planning and scheduling in the process industry

Mixed Integer Optimization in the Chemical Process Industry

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