Rectilinear Floor Plans

Shekhawat, Krishnendra; Duarte, José Pinto

doi:10.1007/978-981-10-5197-5_22

Cited by 3 publications

(1 citation statement)

References 18 publications

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“…On the one hand, a panoply of different algorithmic methods have been used to tackle such problems. They range from logic programming [16], constraint programming [7], quadratic programming [21], over using shape rules and grammars [10,12,28] or graphtheoretic tools [18,22,23] to evolutionary algorithms [12,15] to name just a few. We refer the interested reader to the surveys by Del Río-Cidoncha et al [8] and by Lobons and Donath [17].…”

Section: Related Workmentioning

confidence: 99%

Algorithms for Floor Planning with Proximity Requirements

Klawitter¹,

Klesen²,

Wolff³

2021

Preprint

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Floor planning is an important and difficult task in architecture. When planning office buildings, rooms that belong to the same organisational unit should be placed close to each other. This leads to the following NP-hard mathematical optimization problem. Given the outline of each floor, a list of room sizes, and, for each room, the unit to which it belongs, the aim is to compute floor plans such that each room is placed on some floor and the total distance of the rooms within each unit is minimized. The problem can be formulated as an integer linear program (ILP). Commercial ILP solvers exist, but due to the difficulty of the problem, only small to medium instances can be solved to (near-) optimality. For solving larger instances, we propose to split the problem into two subproblems; floor assignment and planning single floors. We formulate both subproblems as ILPs and solve realistic problem instances. Our experimental study shows that splitting the problem helps to reduce the computation time considerably. Where we were able to compute the global optimum, the solution cost of the combined approach increased very little.

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