A robust model for multi-floor layout problem

Izadinia, Niloufar; Eshghi, Kourosh; Salmani, Mohammad Hassan

doi:10.1016/j.cie.2014.09.023

Cited by 26 publications

(4 citation statements)

References 20 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Their PCG method can reduce the resources required for development and can personalize the 3-Dimentional virtual environments. Amine et al [35] developed a Mixed Integer Programming (MIP) robust model for a form of Multi-floor layout problem. In the experiment, they created facility layouts reflecting the relationship between the cellar containing main storages and upper floors in which departments will be located in predetermined locations.…”

Section: B Reinforcement Learningmentioning

confidence: 99%

Towards Automatic Facility Layout Design Using Reinforcement Learning

Ikeda¹,

Nakagawa²,

Tsuchiya³

2022

Annals of Computer Science and Information Systems

View full text Add to dashboard Cite

The accuracy and perfection of layout designing significantly depend on the designer's ability. Quick and nearoptimal designs are very difficult to create. In this study, we propose an automatic design mechanism that can more easily design layouts for various unit groups and sites using reinforcement learning. Specifically, we devised a mechanism to deploy units to be able to fill the largest rectangular space in the current site. We aim to successfully deploy given units within a given site by filling a part of the site. We apply the mechanism to the three sets of units in benchmark problems. The performance was evaluated by changing the learning parameters and iteration count. Consequently, it was possible to produce a layout that successfully deployed units within a given one-floor site.

show abstract

Section: B Reinforcement Learningmentioning

confidence: 99%

Towards Automatic Facility Layout Design Using Reinforcement Learning

Ikeda¹,

Nakagawa²,

Tsuchiya³

2022

Annals of Computer Science and Information Systems

View full text Add to dashboard Cite

show abstract

“…annealing algorithm related departments within each bay are specified, the problem becomes more simple and straightforward to deal with (Wong, 2010). Some reasons necessitate the study of the multi-floor dynamic facility layout problem (MF-DFLP), one of which is the lack of sufficient spaces in cities and high costs related to space supply (Izadinia et al, 2014). Another reason is the commitment of the production industries to respond quickly to the frequent changes in product diversity and demands (Dong et al, 2009).…”

Section: Simulatedmentioning

confidence: 99%

“…Hathhorn et al (2013) presented a multi-objective mixed-integer programming model to minimize the MHCs and the total construction cost of the facility at the same time. Izadinia et al (2014) provided a robust model to be used for the multi-floor facility layout with uncertain material flow between the departments and the storage. Khosravian Ghadikolaei and Shahanaghi (2013) studied MF-DFLP and solved it using a SA algorithm.…”

Section: Literature Reviewmentioning

confidence: 99%

A mathematical model and a simulated annealing algorithm for unequal multi-floor dynamic facility layout problem based on flexible Bay structure with elevator consideration

Zolfi

Jouzdani

2022

JFM

View full text Add to dashboard Cite

Purpose As far as the authors know, no research has already been carried out on the multi-floor dynamic facility layout problem (MF-DFLP) in the continuous form regarding the flexible bay structure, the number and the variable location of the elevator. Therefore, the present paper models the given problem and attempts to find a sub-optimal solution for it using a meta-heuristic simulated annealing (SA) algorithm. Design/methodology/approach The efficient use of resources has always been a prominent matter for decision-makers. Many reasons including land use, construction considerations and proximity of departments have led to the design of multi-floor facilities. On the other hand, their fast-evolving environment calls for dynamic planning. Therefore, in this paper, a model and the SA algorithm for MF-DFLP are presented. Findings After presenting a mathematical model, the problem was solved precisely in a small size using the GAMS software. Also, a near-optimal solution method using a SA meta-heuristic algorithm is suggested and the proposed algorithm was run in the MATLAB software. To evaluate the presented model and the proposed solution, some test cases were considered in two aspects. The first aspect was the test cases that are newly generated in small, medium and large sizes to compare the exact optimal solution with the results of the meta-heuristic algorithm. Eight test cases with small sizes were solved using the GAMS software, the optimum solutions were obtained in a reasonable time, and the cost of their solutions was equal to that of the SA algorithm. Eight test cases with medium sizes were run in the GAMS software with the time limit of 80,000 s, and the SA algorithm had performed better for these test cases. Two test cases were also considered in large size that GAMS could not solve them, whereas the SA algorithm successfully found a proper solution for each. The second aspect included the test cases from the literature. The result showed that suggested algorithm is more capable of finding best solutions than compared algorithms. Originality/value In this paper, an unequal area MF-DFLP was studied in a continuous layout form in which the location and number of the elevators were considered to be variable, and the layouts were considered with flexible bay structure. These conditions were investigated for the first time.

show abstract

“…For completeness, we also mention the robust model in [49] in which some of the usual parameters are considered to be uncertain, and the model in [81] that takes into account safety distances in the event of an explosion.…”

Section: Survey Of the Literaturementioning

confidence: 99%

Mathematical optimization approaches for facility layout problems: The state-of-the-art and future research directions

Anjos

Vieira

2017

European Journal of Operational Research

160

View full text Add to dashboard Cite

Facility layout problems are an important class of operations research problems that has been studied for several decades. Most variants of facility layout are NP-hard, therefore global optimal solutions are difficult or impossible to compute in reasonable time. Mathematical optimization approaches that guarantee global optimality of solutions or tight bounds on the global optimal value have nevertheless been successfully applied to several variants of facility layout. This review covers three classes of layout problems, namely row layout, unequal-areas layout, and multifloor layout. We summarize the main contributions to the area made using mathematical optimization, mostly mixed integer linear optimization and conic optimization. For each class of problems, we also briefly discuss directions that remain open for future research.

show abstract

A robust model for multi-floor layout problem

Cited by 26 publications

References 20 publications

Towards Automatic Facility Layout Design Using Reinforcement Learning

Towards Automatic Facility Layout Design Using Reinforcement Learning

A mathematical model and a simulated annealing algorithm for unequal multi-floor dynamic facility layout problem based on flexible Bay structure with elevator consideration

Mathematical optimization approaches for facility layout problems: The state-of-the-art and future research directions

Contact Info

Product

Resources

About