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- W4313044080 abstract "Graph-based representations of functional requirements (adjacencies, bubble diagram) are a common and useful method that supports architects in the conceptual phase of planning. However, the task of specifying the functional requirements through an adjacency graph can be challenging due to a quadratic growth of complexity in relation to the number of spaces. In turn, this increase of complexity challenges the designer searching for solutions that fulfill these functional requirements. There are systems that aim to address the difficulties related to graph-based space allocation. They, for instance, use fuzzy logic to weight the edges of a graph (i.e., specify relations between spaces) and spring systems (Newtonian gravitation model) to visually clarify the resulting proximity of all spaces according to the rules. Nevertheless, the problem of specifying large-scale adjacencies itself is omitted due to the assumption that such matrices are correctly filled in some previous steps. Moreover, the translation of the resulting graph into a spatial configuration is rarely supported. This work addresses these limitations and proposes a set of tools to assist the designer when defining the adjacency requirements and searching for design solutions that fulfill these requirements. Our approach aims to reduce the complexity of the design task by using graph centrality-based design heuristics. We discuss these heuristics and show their application in a scenario where a new spatial program needs to be allocated into an existing building." @default.
- W4313044080 created "2023-01-06" @default.
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- W4313044080 date "2022-01-01" @default.
- W4313044080 modified "2023-10-02" @default.
- W4313044080 title "Space Matcher - An interactive toolbox for assisting in spatializing & testing office programmes using graph centralities" @default.
- W4313044080 doi "https://doi.org/10.52842/conf.ecaade.2022.2.039" @default.
- W4313044080 hasPublicationYear "2022" @default.
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