Abstract
Indoor room optimal allocation is of great importance in geographic information science (GIS) applications because it can generate effective indoor spatial patterns that improve human behavior and efficiency. However, few research concerning indoor room optimal allocation has been reported. Using an office building as an example, this paper presents an integrative approach for indoor room optimal allocation, which includes an indoor room allocation optimization model, indoor connective map design, and a multiple ant colony optimization (MACO) algorithm. The mathematical optimization model is a minimized model that integrates three types of area-weighted costs while considering the minimal requirements of each department to be allocated. The indoor connective map, which is an essential data input, is abstracted by all floor plan space partitions and connectivity between every two adjacent floors. A MACO algorithm coupled with three strategies, namely, (1) heuristic information, (2) two-colony rules, and (3) local search, is effective in achieving a feasible solution of satisfactory quality within a reasonable computation time. A case study was conducted to validate the proposed approach. The results show that the MACO algorithm with these three strategies outperforms other types of ant colony optimization (ACO), Genetic Algorithm (GA), and particle swarm optimization (PSO) algorithms in quality and stability, which demonstrates that the proposed approach is an effective technique for generating optimal indoor room spatial patterns.
Highlights
Humans spend almost 87% of their time indoors [1]
Based on the basic ACO algorithm, this paper proposes multiple ant colony optimization (MACO) to solve the problem of indoor spatial optimal allocation
Similar to city land use allocation, indoor spatial optimal allocation is a complex process in which the complexity of searching for an optimum solution increases enormously with increases in the number of objects to be allocated and the size of the data set
Summary
It is important to conduct research in indoor spaces. Some studies have already been performed, such as representation and space subdivision of indoor spaces [2,3], which provided a thorough technical foundation for further research, such as indoor room optimal allocation. In the problem of indoor room optimal allocation, spatial search approaches are used to allocate specific objects (such as different office departments) to proper indoor space units (such as rooms) to achieve an optimal spatial layout by considering multiple factors, such as spatial convenience and personal preference. Skillful indoor spatial allocation, such as reasonably allocated departments in an office building, can effectively reduce the cost of office communication. To the best of our knowledge, few studies have been conducted that focus on indoor room optimal allocation
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