Floor Layout Planning Using Artificial Intelligence Technique (original) (raw)

A Heuristic Approach for the Automated Generation of Furniture Layout Schemes in Residential Spaces

A variety of heuristic methods and algorithms have been developed for space layout planning problems. Recent efforts to generate furniture layout schemes in existing spatial configurations have mostly relied on exhaustive search and are likely to produce dysfunctional or counter-intuitive solutions. In this paper, we propose a heuristic approach for the automated generation of furniture layout schemes, with specific focus on residential spaces. First, we present an operational definition for furniture entities, space configurations, and space entities. Then we introduce a heuristic algorithm for generating furniture layout schemes based on a set of space subdivision rules, object-object relations, and object-space relations. Using Grasshopper, we generate a group of possible schemes for a sample residential living space. A discussion follows, outlining current limitations, expanding the context of the study, and possibilities for development including the integration of fuzzy logic for inconsistent input datasets.

Accelerating the solving process of optimal layout design using genetic algorithm

2009

The layout design optimization is a complicated process of an architectural design which is concerned with finding feasible locations and size of rooms that meet design requirement and design preference. This paper formulates the optimal layout design as multi+bjective mixed integer programming model using the binary variables and branch & bound technique to determine the best location and size of a group of interrelated rectangular rooms by placing a representative point at the center of the room. Although solving the layout problems using MIP model is easy to formulate and adapt for meeting architectural requirements, the number of iterations to find the optimal solution is still influenced by the number of rooms. For this reason, we decrease the number of iterations by accelerating branch and bound process. The genetic algorithm has been adopted to find a candidate sequence of branching variables which helps reducing the search tree. Fkom the empirical test, we found that the iterations can be reduced significantly.

A genetic algorithm application for automatic layout design of modular residential homes

This work presents an evolutionary approach that enables the automatic design of modular residential homes in mass customized production. Given a set of modular placement rules for the design, the formal problem can be viewed as a two-dimensional single large object placement problem with fixed dimensions and additional positioning constraints. This formulation results in the search of a floor plan layout constrained by dimensional and positional restrictions over a combinatorial size search space. A genetic algorithm strategy for the automation of floor plan design was implemented and shown to deliver the required design solution layouts. The layouts, when embedded into a proper graphical interface system will allow for future owners to acquire houses fitting their exact needs at affordable prices, improving the quality of living while simultaneously complying with a language of design.

Use of Genetic Algorithm in Layout Design

Acta logistica

Within the design of production layout, the planners are often confronted with complex, sometimes conflicting demands and a number of restrictive conditions, which encourages their efforts to develop new, progressive approaches to the development of production layouts. The purpose of the innovative approaches in this field is to provide users with better, elaborated designs in less time, while they are able to implement various restrictive conditions and company priorities to the design. One of the ways is a use of metaheuristic algorithms by space solution optimisations of manufacturing and logistics systems. These methods have higher quality results compared to classical heuristic methods. Genetic algorithms belong to this group. Main goal of this article is to describe the Genetic Algorithm Layout Planner (GALP) that was developed by authors, and its experimental verification and comparison with results of the classical heuristic.

Assistant Tool for Architectural Layout Design by Genetic Algorithm

2006

Architectural design is a very complicated process. It contains many sequences within the design process that the architects have to take into considerations. Within the process, the architect will look for every feasible schematic to make the best decision for developing the final design process. However, the preliminary design involves both conceptual and schematic design that concern about quantitative analysis and qualitative analysis. The objective of this research is to utilize an assistant method or tool to help form a preliminary design and a thinking process by using genetic algorithm to find the feasible solutions for conceptual and schematic design.

Space layout planning using an evolutionary approach

Artificial Intelligence in Engineering, 1998

This paper describes a design method based on constructing a genetic/evolutionarydesign model whose idea is borrowed from natural genetics. Two major issues from the modelling involve how to represent design knowledge for the evolutionary design model and the usefulness of the model for design problems. For the representation of design knowledge in the model, a schema concept is introduced. The utility of the model is based on its computational efficiency and its capability of producing satisfactory solutions for the given set of problem requirements. The design problem used to demonstrate the approach is a large office layout planning problem with its associated topological and geometrical arrangements of space elements. An example drawn from the literature is used.

Optimization of architectural layout by the improved genetic algorithm

Journal of Civil Engineering and Management - J CIV ENG MANAG, 2005

In this paper we consider architectural layout problem that seeks to determine the layout of Units based on lighting, heating, available sizes and other objectives and constraints. For a conceptual design of architectural layout we present an approach based on evolutionary search method known as the genetic algorithms (GAs). However, the rate of convergence of GAs is often not good enough at their current stage. For this reason, the improved genetic algorithm is proposed. We have analysed and compared the performance of standard and improved genetic algorithm for architectural layout problem solutions and presented the results of performance.

Software Implementation and Experimentation with a New Genetic Algorithm for Layout Design

Journal of Industrial and Systems Engineering, 2009

This paper discusses the development of a new GA for layout design. The GA was already designed and reported. However the implementation used in the earlier work was rudimentary and cumbersome, having no suitable Graphical User Interface, GUI. This paper discusses the intricacies of the algorithm and the GA operators used in previous work. It also reports on implementation of a new GA operator which was not included in earlier reports. The software was then used to conduct a series of experimentations to establish the best configuration of the operators for better results. The paper is also demonstrating a comparison of the new GA results and results from the literature. In addition the results show the solution of two new problems by various methods from the author’s own layout developments in industry. The results demonstrate that in most cases the new GA is superior to the existing methods. In particular the speed of the new GA is achieving a reasonable solution is significantly ...

A enhanced algorithm for floorplan design using evolutionary technique

Artificial Intelligence Research, 2012

Floor planning is an important problem in very large scale integrated-circuit (VLSI) design automation domain as it evaluates the performance, size, yield and reliability of ICs. Due to rapid increase in number of components on a chip, floor planning has gained its importance further in determining the quality of the design achieved. In this paper we have devised an approach for placement of modules in a given area with bounding constraints in terms of minimum placement area imposed. We have used Modified Genetic Algorithm (MGA) technique for determining and obtaining an optimal placement using an iterative approach.