A proposal for selecting target buildings for the reorganization of public housing using a depth-first search algorithm with recursive functions

Abstract

We improved a method to support more general and rational reorganization planning, demonstrating its practicality through application to Kobe municipal housing complexes. We initially developed a cost-effective algorithm using depth-first search, enabling the consideration of a larger pool of dwelling units and houses for reorganization. We then ensured the algorithm accounts for practical constraints by grouping sale sites together and considering proximity to roads, thereby deriving more viable combinations. Furthermore, we clarified the break-even point for the reorganization projects, allowing for an assessment of project feasibility from a profitability standpoint.