Crane Scheduling of Steel-making and Continuous Casting Process Using the Mixed-Timed Petri Net Modelling Via CPLEX Optimization

Liu, Wei; Chai, Tianyou; Wang, Hong; Zheng, Binglin

doi:10.3182/20110828-6-it-1002.00170

Cited by 9 publications

(3 citation statements)

References 6 publications

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“…Moreover, [6] proposes a specific PN system of iron and steel process, to analyze the performances of the iron and steel process. However, the paper [5] analyzes the performances of a specific resource of the SM-CC process and lacks generality. Moreover, the model presented in [6] is hard to describe and to apply to real systems.…”

Section: Introductionmentioning

confidence: 99%

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Modeling Steelmaking and Continuous Casting plants by Timed Petri Nets

Fanti

Mangini

Rotunno

et al. 2013

2013 IEEE 18th Conference on Emerging Technologies &Amp; Factory Automation (ETFA)

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In this paper we deal with the problem of modeling and simulating the Steelmaking and Continuous Casting (SM-CC) processes. The SM-CC production processes are very complex and exhibit production cycles that have to be managed with suitable sequencing and scheduling procedures in order to minimize blocking and bottleneck conditions. The paper describes in details the SM-CC process by a modular approach in a Timed Petri Net framework. In order to show that the modeling procedure is suitable to describe large systems, we model and simulate a real case study involving a SM-CC plant located in the North of Italy.

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Section: Introductionmentioning

confidence: 99%

“…Sun et al [5] propose a mixed TPN model in order to improve the performances of the crane scheduling problem. Moreover, [6] proposes a specific PN system of iron and steel process, to analyze the performances of the iron and steel process.…”

Section: Introductionmentioning

confidence: 99%

Modeling Steelmaking and Continuous Casting plants by Timed Petri Nets

Fanti

Mangini

Rotunno

et al. 2013

2013 IEEE 18th Conference on Emerging Technologies &Amp; Factory Automation (ETFA)

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“…It is also important to properly select the model solution parameters. For example, Sun et al [14] use CPLEX a branch-and-cut method in their work for optimization of firing transition sequences, based on the Mixed-timed Petri net [15]. In our realizations, we used the CPLEX optimization package (see Section 6).…”

Section: Introductionmentioning

confidence: 99%

Modified L-shaped Decomposition Method with Scenario Aggregation for a Two-Stage Stochastic Programming Problem

Ušpurienė

Sakalauskas

Gricius

2018

ITC

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This paper introduces a method which is developed to solve two-stage stochastic programming problems in which first-stage region is unbounded and cannot be solved using traditional decomposition. We are using our proposed L-shaped decomposition method modification to solve such problems. In order to achieve a more accurate result, the number of scenarios generated in the optimization process must be large enough. If there is a large number of target variables, optimization takes a long time and uses a lot of resources. Thus, in order to reduce the number of iterations of the optimization process, the amount of resources used, and the calculating time needed to get the optimal solution, the aggregation approach is applied. This paper also presents results of our research on optimal parameters setting of the proposed method.

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Multiple-Crane Integrated Scheduling Problem with Flexible Group Decision in a Steelmaking Shop

Xie

Zheng²

2017

Intelligent Computing Methodologies

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Crane Scheduling of Steel-making and Continuous Casting Process Using the Mixed-Timed Petri Net Modelling Via CPLEX Optimization

Cited by 9 publications

References 6 publications

Modeling Steelmaking and Continuous Casting plants by Timed Petri Nets

Modeling Steelmaking and Continuous Casting plants by Timed Petri Nets

Modified L-shaped Decomposition Method with Scenario Aggregation for a Two-Stage Stochastic Programming Problem

Multiple-Crane Integrated Scheduling Problem with Flexible Group Decision in a Steelmaking Shop

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