Automated facilities Layout Programs

Seehof, Jerrold M.; Evans, Wayne Ο.; Friederichs, James W.; Quigley, James J.

doi:10.1145/800256.810696

Cited by 14 publications

(8 citation statements)

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“…Well-known examples are represented by automated facilities layout (cf. Chen et al, 2020;Levary & Kalchik, 1985;Liggett, 2000;Seehof et al, 1966, among many others), spatial synthesis (cf. Eastman, 1975;Jo & Gero, 1998;Veloso & Krishnamurti, 2021), space planning (cf.…”

Section: What Are Self-organizing Floor Plans?mentioning

confidence: 99%

Self-Organizing Floor Plans

Carta

2021

Harvard Data Science Review

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This article introduces and comments on some of the techniques currently used by designers to generate automatic building floor plans and spatial configurations in general, with emphasis on machine learning and neural networks models. This is a relatively new tendency in computational design that reflects a growing interest in advanced generative and optimization models by architects and building engineers.The first part of this work contextualizes self-organizing floor plans in architecture and computational design, highlighting their importance and potential for designers as well as software developers. The central part discusses some of the most common techniques with concrete examples, including Neuro Evolution of Augmenting Topologies (NEAT) and Generative Adversarial Networks (GAN). The final section of the article provides some general comments considering pitfalls and possible future developments, as well as speculating on the future of this trend.

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Section: What Are Self-organizing Floor Plans?mentioning

confidence: 99%

Self-Organizing Floor Plans

Carta

2021

Harvard Data Science Review

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“…Facility layout problems are similar to plant layout problems, considering flows between departments in offices, or manufacturing and assembly. Some of the early work in this field includes (Rosenblatt, 1979) who combines the early work of allocating facilities quantitatively using material handling costs (E.S Buffa, 1964) and qualitative work on subjective closeness ratings (Seehof et al, 1966). Many works have extended this to develop extra capabilities such as considering multi-floor layouts (Bozer et al, 1991).…”

Section: Literature Review Of Layout Optimizationmentioning

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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“…Many approaches to solving FLP may be generally divided into two classes: constructive and improvement-based. In the former group, consecutive objects are inserted into the layout one by one (e.g., ALDEP proposed by Seehof et al, 1966 or CORELAP created by Parsaei and Galbiati, 1987) whereas in the latter case, the initial arrangement of all items is repeatedly improved by exchanging their locations (e.g., CRAFT). Hybrid methods involve both techniques.…”

Section: / 26mentioning

confidence: 99%

A novel version of simulated annealing based on linguistic patterns for solving facility layout problems

Grobelny

Michalski

2017

Knowledge-Based Systems

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The paper presents a novel version of the simulated annealing algorithm based on linguistic patterns (LP) and fuzzy theory approach. The article describes shortly the linguistic patterns and shows on a simple illustrative example the idea of using the Łukasiewicz formula as a criterion for the facility layout optimization. Next, the detailed description of our LP version of simulated annealing is presented. The influence of the proposed algorithm parameters on the effectiveness of our approach is then examined in a simulation experiment involving four different types of facility layout problems. The outcomes from the first experiments are used for optimally setting the parameters of our proposal in the second simulation study focused on verifying its effectiveness for objects with uniform and variable sizes. The obtained results show that the presented procedure, apart from producing decent results in terms of the classic goal function and the linguistic pattern criterion, provided solutions that were qualitatively different than those generated by a crisp version.

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Automated facilities Layout Programs

Cited by 14 publications

References 0 publications

Self-Organizing Floor Plans

Self-Organizing Floor Plans

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

A novel version of simulated annealing based on linguistic patterns for solving facility layout problems

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