Combinatorial framework for effective scheduling of multipurpose batch plants

Sanmartí, Eduard; Puigjaner, Luís; Holczinger, Tibor; Friedler, Ferenc

doi:10.1002/aic.690481115

Cited by 50 publications

(57 citation statements)

References 19 publications

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“…This approach has been further developed by Sanmarti et al [148] into S-graphs. Scheduling problems have been solved also for batch water networks.…”

Section: Contributions From Pres Conferencesmentioning

confidence: 48%

Process integration, modelling and optimisation for energy saving and pollution reduction

Friedler

2010

Applied Thermal Engineering

145

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“…This approach has been further developed by Sanmarti et al [148] into S-graphs. Scheduling problems have been solved also for batch water networks.…”

Section: Contributions From Pres Conferencesmentioning

confidence: 48%

Process integration, modelling and optimisation for energy saving and pollution reduction

Friedler

2010

Applied Thermal Engineering

145

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“…Sanmarti et al use a graph representation called the S-Graph for specifying specific chemical processes in multipurpose batch plants [13,14]. Their approach demonstrates how graphs are well suited for modelling complex scenarios as in this case they model a flexible environment where the number of products is very large and where alternative paths may be used to manufacture the same product.…”

Section: Production Line Graph Modellingcontrasting

confidence: 40%

Manufacturing Production Line Modelling and Classification of Associated NP-Hard Problems

Bonello¹,

Abela²,

Cachia³

2018

Int J Comput Softw Eng

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The purpose and scope of this studyThis study was part of a two-year research project financed by the European Regional Development Fund (ERDF) called Research Services in Manufacturing: ICT in Manufacturing. The objective of this process was to create a software solution that allows operators to model production lines and determine and classify the scheduling problems represented by the model. It has long been felt that not enough information is available regarding the scheduling problems affecting the manufacturing industry in Malta. This project was undertaken to gain additional information on the state of scheduling in the local manufacturing industry and to provide an extensible framework that can be used for current analysis and future research.This study focused on providing a graphical means of representing scheduling problems. This representation describes the abstraction of the production line involved in manufacturing a product. The second aim of the study is to create a set of heuristics using the model to classify the scheduling problem according to its computational complexity, and when possible, pointing to the relevant literature used to derive the classification in order to help researchers understand the problem better.Scheduling involves efficient utilisation of scarce resources. While this study focuses on scheduling in manufacturing industry, Leung draws a parallel to the problems encountered by computer scientists in the 1960s when computational resources (CPU, memory and I/O devices) were scarce [8]. This results of this study are of interest to computer scientists, operators in the manufacturing industry whose work deals with scheduling and to researchers in the field of optimisation. AbstractOptimisation of production lines is known to be NP-Hard in the general case so many near-optimal approximation algorithms have been researched to overcome the challenge [1]. In this paper we describe an approach to modelling production lines using a graph theoretic model. In particular, we focus on single machine and job shop problems. We show that the model can be extended to open shop problems. We also discuss how the model can be used to classify scheduling problems from the generated models. Int J Comput Softw EngIJCSE, an open access journal

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“…These systems are discussed in more detail in [4], [6], [7], [10], [11], [12]. This model can be used for several applications including flowshops, chemical processing plants, and services.…”

Section: Introductionsupporting

confidence: 39%

Model reduction for a class of input-quantized systems in the max-plus algebra

Weyerman

Warnick

2008

2008 47th IEEE Conference on Decision and Control

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Abstract-We present a systematic method for model reduction of a class of input-quantized systems in the max-plus algebra. We consider a generalization of the flow shop with finite intermediate storage. These systems are useful in modeling chemical processes and manufacturing systems, including pharmaceutical manufacturing, construction, propellant manufacturing and assembly lines. The makespan minimization problem we consider is N P-complete. Our method of model reduction reduces the number of states that a system can reach, thus reducing the search space for the optimization problem. This allows us to construct a smaller N P-complete problem to approximate the solution to the larger problem. We show that the error of the approximation is bounded and that as the approximated system approaches the true system, that the error of the approximation goes to zero.

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Combinatorial framework for effective scheduling of multipurpose batch plants

Cited by 50 publications

References 19 publications

Process integration, modelling and optimisation for energy saving and pollution reduction

Process integration, modelling and optimisation for energy saving and pollution reduction

Manufacturing Production Line Modelling and Classification of Associated NP-Hard Problems

Model reduction for a class of input-quantized systems in the max-plus algebra

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