Efficient Solution Approaches for the Multifloor Process Plant Layout Problem

Patsiatzis, Dimitrios I.; Papageorgiou, Lazaros G.

doi:10.1021/ie020586t

Cited by 35 publications

(27 citation statements)

References 25 publications

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“…Papageorgiou & Rotstein extended this model to consider a continuous domain single floor MILP model (Papageorgiou and Rotstein, 1998). Patsiatzis & Papageorgiou then extended it further to multi floor (Patsiatzis and Papageorgiou, 2002a) and developed a decomposition and an iterative approach (Patsiatzis and Papageorgiou, 2003). The decomposition approach is largely more accurate and expensive in processing time, while the iterative approach is the reverse.…”

Section: Mathematical Programming Approachesmentioning

confidence: 99%

Module layout optimization using a genetic algorithm in light water modular nuclear reactor power plants

Wrigley

Wood

Stewart

et al. 2019

Nuclear Engineering and Design

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The Small Modular Reactor (SMR) concept has been proposed to solve some of the construction problems of large reactors. SMRs are designed to be "shop fabricated and then transported as modules to the sites for installation". As a consequence they theoretically have shorter build schedules and require less capital investment (Locatelli et al., 2014). A literature review has highlighted a lot of work has been undertaken in the research and development of different types of reactors and reactor modules but the design of balance of plant modules has not been extensively researched (Wrigley et al., 2018). The focus of this paper will be on a case study for balance of plant modules in a light water reactor. Wrigley et al., (2018) highlighted two methods of modularization for balance of plant modules in nuclear reactors to support modularization for SMRs. If the modules are to be designed for factory build and transport in a standardized grid approach, a design method needs to be developed to help achieve this approach. To enable this, we propose a three step method: how to group components into modules, how to layout the modules and how to arrange components inside the modules. The Shearon Harris Nuclear Power Plant was chosen for its publically available data. A previous study on this plant used matrix reordering techniques to group components and heuristically assign them to large modules, highlighting a potential capital cost savings of 15%. A method of assigning components to modules could be developed in future studies, but this was not the focus of this paper. We therefore use the same allocation of components and modules as the previous study but tackle how balance of plant modules

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Section: Mathematical Programming Approachesmentioning

confidence: 99%

Module layout optimization using a genetic algorithm in light water modular nuclear reactor power plants

Wrigley

Wood

Stewart

et al. 2019

Nuclear Engineering and Design

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“…It is known that pressure and velocity of each branch pipeline are respectively equal at branch points by the fluid continuity property. For the branch point 1 and the branch i at branch point 1, the following equation can be obtained by equation (2), (4) and the relationship between fluid flow and fluid velocity.…”

Section: B Evaluation Model For Pipeline With Branches (Empb)mentioning

confidence: 99%

“…Generate the corresponding random sequence point according to Monte Carlo sampling model. 4. Map the random sequence points to the node and retain sampling.…”

Section: A the Monte Carlo Modelmentioning

confidence: 99%

“…At present, the pipeline design mainly includes the expert system, mathematical programming, genetic evolution, etc. Some scholars have applied these methods to the engineering field, and achieved good effect [4][5][6]. However, so far, the optimization design mainly concerned material cost of pipelines, but ignored the running cost of pipelines.…”

Section: Introductionmentioning

confidence: 99%

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Optimization design for complex pipelines inside electromechanical products based on flow resistance loss

Feng

Lyi

2014

2014 IEEE International Conference on Information and Automation (ICIA)

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Optimization design for complex pipelines inside electromechanical products is a very difficult task within complex products such as cars, planes, ships and rockets. Thus, an optimization design for complex pipelines is proposed based on the flow resistance loss in this paper. The basic framework of the design includes three parts like pre-processing, evalution model and optimization search algorithm. Firstly, Monte Carlo pre-processing model is established to effectively reduce the complexity of the optimizaton design. Also, flow resistance loss model of complex pipelines with branches is constructed to evaluate design. Moreover, a novel particle swarm optimization (PSO) algorithm is presented to find an approximate optimal design. Finally, the comparison experiments and examples demonstrate that the optimization design is effective and practical.

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“…Previous simultaneous approaches were only able to solve layout problems having less than 11 units in reasonable computational times. Decomposition approaches (Patsiatzis and Papageorgiou, 2003), constructionbased methods (Xu and Papageorgiou, 2007) with improvement phases (Xu and Papageorgiou, 2009), and a number of evolutionary methods (Furuholmen et al, 2010, Kheirkhah et al, 2015, Nabavi et al, 2016, Park and Lee, 2015 have successfully addressed large-sized layout problems in shorter times, but globally optimal solutions are not guaranteed. Recently, more ecient multi-oor layout models were developed by Ejeh et al (2018a) incorporating connection, pumping, area-dependent land and oor construction costs in the layout design of process plants having tall equipment.…”

Section: Introductionmentioning

confidence: 99%

Optimal layout of multi-floor process plants using MILP

Ejeh

Liu

Papageorgiou

2019

Computers & Chemical Engineering

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In this work, a new mixed integer linear programming (MILP) model is proposed for the multi-oor process plant layout problem with additional considerations. Multi-oor process plant layout determines the spatial arrangement of process plant units considering their connectivity amongst other factors and aects the cost of constructing the plant, the ease of plant operation and expansion, general safety levels within the plant and its neighbouring environment, as well as operational costs. Over the past years, mathematical programming models have been developed to describe the layout problem considering connectivity costs, pumping costs, installation of safety devices, and piping, in single and multiple oors. Features such the representation of irregularly shaped items, tall equipment spanning multiple oors and others have been successfully modelled. This work builds on such past considerations with additional features that allow multi-oor equipment items extend above the maximum potential number of oors, and the selection of an available number of oors less than the maximum number required by any equipment item. Integer cuts are also developed for the proposed model to enhance its eciency. The performance and limitations of the proposed model are demonstrated with industry-relevant case studies of up to 25 units, and results show a potential cost savings when compared to existing models with additional computational benets of the integer cuts in all of the cases explored.

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Efficient Solution Approaches for the Multifloor Process Plant Layout Problem

Cited by 35 publications

References 25 publications

Module layout optimization using a genetic algorithm in light water modular nuclear reactor power plants

Module layout optimization using a genetic algorithm in light water modular nuclear reactor power plants

Optimization design for complex pipelines inside electromechanical products based on flow resistance loss

Optimal layout of multi-floor process plants using MILP

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