A solution to the facility layout problem using simulated annealing

Chwif, Leonardo; Barretto, Marcos Ribeiro Pereira; Moscato, Lucas Antonio

doi:10.1016/s0166-3615(97)00106-1

Cited by 86 publications

(30 citation statements)

References 30 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Literature has specified the use of artificial neural networks (Chung, 1999, Heragu and Kusiak, 1988, Kim and Kim, 2000; construction heuristics such as CORELAP (Lee and Moore, 1967) , ALDEP (Seehof and Evans, 1967), COFAD (Tompkins and Reed, 1976), SHAPE (Hassan, 1994); improvement heuristics such as CRAFT (Armour and Buffa, 1963), FRAT (Khalil, 1973) and DISCON (Drezner, 1987); tabu search algorithms (Chiang and Kouvelis, 1996), simulated annealing algorithms (Chwif et al, 1998, genetic algorithms (Pierreval et al, 2003, Dunker et al, 2005, Balakrishnan et al, 2003, slicing tree (Shayan andChittilappilly, 2004, Wu andAppleton, 2002), space filling curves (Wang et al, 2005), ant colony algorithms (Solimanpur et al, 2005, Baykasoglu et al, 2006 and hybrid genetic algorithms (Mir and Imam, 2001, Balakrishnan et al, 2003.…”

Section: Some Advances In Digital Factory Design Methodsmentioning

confidence: 99%

Resource selection ontologies in support of a recipe-based factory design methodology

Agyapong-Kodua

Haraszkób

Németh

2014

International Journal of Production Research

View full text Add to dashboard Cite

Factory (re) design involves the appropriate utilisation of product, process and resource knowledge in the determination of suitable configurations of physical factory facilities which have the potential to meet industrial and organisational requirements. Different independent semantic modelling standards exist for products, processes and resources but to automate and facilitate the selection of factory resources, there is the need to semantically integrate resource capabilities with product and process requirements. This paper defines a 'recipe-based' approach to designing factories and it is based on the assumption that capabilities and competences of reusable components (or building blocks) of factory resources can be semantically modelled and matched with product-process requirements. This approach will enable Factory Designers and Engineers to decide on relevant resource systems within finite, valuable and defined sets of requirements.

show abstract

Section: Some Advances In Digital Factory Design Methodsmentioning

confidence: 99%

Resource selection ontologies in support of a recipe-based factory design methodology

Agyapong-Kodua

Haraszkób

Németh

2014

International Journal of Production Research

View full text Add to dashboard Cite

show abstract

“…Among metaheuristics approaches, one can distinguish global search methods, such as Tabu Search [20] and Simulated Annealing [21], evolutionary methods, such as Ant Colony Optimization [22] and the popular GA [23], and a hybridization of different metaheuristics [24].…”

Section: B Resolution Approachesmentioning

confidence: 99%

A Facility Layout Planner tool based on Genetic Algorithms

Pinto

Gonçalves²,

Cardoso³

et al. 2016

2016 IEEE Symposium Series on Computational Intelligence (SSCI)

View full text Add to dashboard Cite

Abstract-Nowadays, in order to maintain their competitiveness, manufacturing companies must adapt their production methods quickly, with minimum expenditure, to frequent variations on demand. With the shortage of the product life time, flexibility, efficiency and reusability of industrial processes are important factors, which may determine the survival of the company. The ReBORN project is working around these ideas, namely studying how can an old production equipment be reused into new contexts. The ReBORN Workbench is a simulation tool for factory layout design, which generates solutions based on the production requirements and facilities' availability, corresponding Life Cycle Assessment, and associated location cost. This paper is concerned with the ReBORN Workbench module responsible to generate solutions for equipment location, generally know as Facility Layout Problems. A Genetic Algorithm was implemented to solve these problems, which aims to minimize the total material handling costs. The effectiveness of the proposed approach is evaluated with a numerical example and compared with other similar approaches. The results show that the proposed approach is indeed effective to solve problems regarding facilities layout.

show abstract

“…It has been applied successfully to a wide variety of highly complicated combinatorial optimization problems (Abramson 1991, Chwif, et al 1998, Jayaraman and Ross 2003, Lim, et al 2006, Lin, et al 2007, McKendall Jr., et al 2006, Van Breedam 1995 as well as various real-world problems (Candalino Jr., et al 2004, Kim and Moon 2003, Lee, et al 2007). SA was introduced by Metropolis et al (1953) and popularized by Kirkpatrick et al (1983).…”

Section: Simulated Annealing Heuristic For the Ttrptwmentioning

confidence: 99%