PSOLA: A Heuristic Land-Use Allocation Model Using Patch-Level Operations and Knowledge-Informed Rules

摘要: Optimizing land-use allocation is important to regional sustainable development, as it promotes the social equality of public services, increases economic benefits activities, and reduces ecological risk planning. Most optimization models allocate using cell-level operations that fragment patches. These do not cooperate well with planning knowledge, leading irrational patterns. This study focuses on building a heuristic model (PSOLA) particle swarm optimization. The allocates patch-level avoid fragmentation. include patch-edge operator, patch-size patch-compactness operator constrain size shape also integrated knowledge-informed rules provide auxiliary knowledge during consist suitability, accessibility, land use policy, stakeholders’ preference. To validate PSOLA model, case was performed in Gaoqiao Town Zhejiang Province, China. results demonstrate outperforms basic PSO (Particle Swarm Optimization) terms social, economic, ecological, overall by 3.60%, 7.10%, 1.53% 4.06%, respectively, which confirms effectiveness our improvements. Furthermore, has an open architecture, enabling its extension generic tool support decision making