Rectangular Floorplans with Block Symmetry

CAADRIA proceedings

For most of the architectural design problems, there are underlying mathematical sub-problems, they may require to consider for generating architectural layouts. One of these sub-problems is to satisfy adjacency constraints for obtaining an initial layout. But in the literature, there does not exist a mathematical procedure that can address any given adjacency requirements, i.e., there does not exist a tool for generating a floor plan corresponding to any given adjacency (planar) graph (there exist algorithms for constructing floor plans for planar triangulated graphs only). In this paper, we are going to present an algorithm that would generate a floor plan corresponding to any given planar graph. The larger aim of this research is to develop a user-friendly tool that can generate a variety of initial layouts corresponding to a given graph, which can be further modified by the architects/designers.

Automation in Construction, 2020

This paper proposes a methodology for the automated construction of rectangular floorplans (RFPs) while addressing dimensional constraints and adjacency relations. Here, adjacency relations are taken in the form of a dimensionless rectangular arrangement (RA) ensuring the existence of a RFP, while dimensional constraints are given in terms of minimum width and aspect ratio range for each room. A linear optimization model is then presented to obtain a feasible dimensioned RFP for user-defined constraints. A GUI is also developed for the automated generation of RFPs. The proposed model is able to generate feasible solutions for every possible RA in a reasonable amount of time. From the architectural prospective, this work can be seen as a re-generation of well-known architectural plans with modified dimensions. At the end, the regeneration of existing legacy RFPs (corresponding to the user defined dimensions) has been demonstrated, taking their image as input.

Advanced Engineering Informatics, 2012

Computer-aided architectural design Floor plan layout Relational algebras Constraint satisfaction Qualitative and quantitative reasoning a b s t r a c t Architectural floor plan layout design is what architects and designers do when they conceptually combine design units, such as rooms or compartments. At the end of this activity, they deliver precise geometric schemas as solutions to particular problems. More research on this topic is needed to develop productive tools. The authors propose orthogonal compartment placement (OCP) as a new approach to this activity. OCP includes a problem formulation and a solution method in which qualitative and quantitative knowledge are combined. Topological knowledge underlies human spatial reasoning. Computers can adequately perform repetitive topological reasoning. We believe that OCP is the first approach in CAAD to incorporate a full relational algebra to generate floor plan layouts. Based on block algebra (BA) and constraint satisfaction (CS), OCP can generate candidate solutions that correspond to distinct topological options. The analysis of a case study using a prototype tool is included.

Artificial Intelligence for Engineering Design, Analysis and Manufacturing, 2018

An important task in the initial stages of most architectural design processes is the design of planar floor plans, that are composed of non-overlapping rooms divided from each other by walls while satisfying given topological and dimensional constraints. The work described in this paper is part of a larger research aimed at developing the mathematical theory for examining the feasibility of given topological constraints and providing a generic floor plan solution for all possible design briefs.In this paper, we mathematically describe universal (or generic) rectangular floor plans with n rooms, that is, the floor plans that topologically contain all possible rectangular floor plans with n rooms. Then, we present a graph-theoretical approach for enumerating generic rectangular floor plans upto nine rooms. At the end, we demonstrate the transformation of generic floor plans into a floor plan corresponding to a given graph.

Journal of Civil Engineering and Management, 2003

Knowledge-based tools assisting the designer in engineering represent further improvement of expert systems. The present paper shows how such software can be developed in the particular domain of floor layout design for buildings. The recently developed paradigm of hierarchical graphs is taken as the knowledge representation scheme. The user of the system is encouraged to undertake the search for rational solution at two levels. First, an analysis of functionality requirements for the designed object is performed. This results in a graph capturing main functions and relations between them. Further, this graph is mapped onto another graph depicting the floor layout in terms of areas and rooms. Both graphs produced by the user are checked against the constraints resulting from the requirements of the relevant code of practice. The final result is converted into the format accepted by a commercial CAD-tool in order to proceed with the detailed design.

ArXiv, 2020

In this paper, we present GPLAN, software aimed at constructing dimensioned floorplan layouts based on graph-theoretical and optimization techniques. GPLAN takes user requirements as input in the following two forms: i. Adjacency graph: It allows user to draw an adjacency graph on a GUI(graphical user interface) corresponding to which GPLAN produces a set of dimensioned floorplans with a rectangular boundary, where each floorplan is topologically distinct from others. ii. Dimensionless layout: Here, user can draw any layout with rectangular or non-rectangular boundary on a GUI and GPLAN transforms it into a dimensioned floorplan while preserving adjacencies, positions, shapes of the rooms. The above approaches represent different ways of inserting adjacencies and GPLAN generate dimensioned floorplans corresponding to the given adjacencies. The larger aim is to provide alternative platforms to user for producing dimensioned floorplans for all given (architectural) constraints, which ...

The main issue we are after here is space layout planning, space layout planning which examine the capability to better utilization of architecture space, this paper will investigate the potentials of evolutionary computation in solving the combinatorial problem of space layout planning; it will focus on the topological level of problems, topological allocation concern with the relationships between two spaces, i.e. the adjacency and proximity between two spaces.

K-dimensional trees, abbreviated as k-d trees in the following, are binary search and partitioning trees which represent a set of n points in a multi-dimensional space . K-d tree data structures have primarily been used for nearest neighbor queries and several other query types for example in database applications. In the context of a research project at the Bauhaus-University Weimar concerned with the development of a creative evolutionary design method for layout problems in architecture and urban design, spatial partitioning with k-d trees has been applied as a partial solution to generate floor plan layouts. Unlike, for example, packing algorithms in [2] and slicing tree structures in [3] the employment of k-d tree algorithms in combination with evolutionary algorithms to generate floor plan layouts has not previously been examined in the scope presented here. In the application developed in this project the k-d tree algorithm is initially used to subdivide a given rectangular area. The dividing lines thereby correspond to eventual spatial boundaries. By combining the k-d tree algorithm with genetic algorithms and evolutionary strategies, layouts can -in the current version -be optimized in three criteria dimensions (size, ratio and topology). Through user interaction the layouts can be dynamically adjusted and altered in real time. The result is a generative mechanism that provides an interesting and promising alternative to existing well-established algorithms for the creative and evolutionary solution of layout problems in architecture and urban design.

arXiv (Cornell University), 2022

Existing graph theoretic approaches are mainly restricted to floor-plans with rectangular boundary. In this paper, we introduce floor-plans with L-shaped boundary (boundary with only one concave corner). To ensure the L-shaped boundary, we introduce the concept of non-triviality of a floor-plan. A floor-plan with a rectilinear boundary with at least one concave corner is non-trivial if the number of concave corners can not be reduced, without affecting the modules adjacencies within it. Further, we present necessary and sufficient conditions for the existence of a non-trivial L-shaped floor-plan corresponding to a properly triangulated planar graph (PTPG) G. Also, we develop an O(n 2 ) algorithm for its construction, if it exists.

This survey methodically analyzes deep learning techniques used in generating floorplan layouts, summarizes current methodologies that shift from image-based to graph-based and multimodal-based methods, and discusses their advantages and drawbacks. The review includes primary datasets with floorplan layout generation tasks and addresses the issues related to geographic diversity, typological variations, and format consistency. Floorplan generation should be approached as an information transmission problem that allows the integration of graphbased methods with other techniques instead of viewing it solely as image generation. Critical opportunities include region-specific dataset development, external contextual factor integration, and enhanced long-range dependency management. The research presented outlines potential future research paths that aim to develop more practical and robust solutions for architectural design.