A Multi-Objective Crossover Parallel Combinatorial Optimization (MCPCO) Model for Site Selection of Catalyst Elements in Urban Micro-Renewal

The site selection of catalyst elements plays a crucial role in urban micro-renewal. Existing site selection models are incapable of configuring multiple types of elements in parallel and exhibit limited capacity in translating urban spatial structures and balancing conflicting stakeholder interests, failing to meet the comprehensive and complex requirements inherent in catalyst element site selection problems. Drawing on the perspectives of urban planning, operations research, and computer science, this study proposes a Multi-objective Ccrossover Parallel Combinatorial Optimization (MCPCO) model for the site selection of catalyst elements, along with a corresponding optimization method. This model uses concise and universal model architecture to map complex and specific real-world problems, optimizing the simultaneous configuration of multiple types of catalyst elements under multiple and conflicting objectives. An empirical study, using the renewal of the Liuhe Confucian Temple historical area in Nanjing as a case study, demonstrates that the model effectively maps and solves the site selection problem of catalyst elements in urban micro-renewal, providing a useful reference for similar problems especially characterized by parallel site selection of multiple types of elements.