Participatory multi-objective optimization for planning dense and green cities
Sergio Wicki, Jonas Schwaab, Ján Perháč, Adrienne Grêt‐Regamey
Abstract
The consideration of urban ecosystem services becomes increasingly important when planning compact cities. We implement a multi-objective optimization approach to support decision-makers in their efforts to develop green and dense cities. Embedded in a participatory process, the applied genetic algorithm allows us to assess spatial tradeoffs between urban ecosystem services and compactness. The optimization model is embedded in a decision support system for interactive analysis and communication of the results, facilitating the engagement of planners to support sustainable development. We illustrate the process in a multi-level case study in Singapore, a tropical city state aiming to pursue its distinct greening strategy. The whole process, from the problem definition to the obtained solution set, is evaluated using a feedback loop with stakeholders. Using this approach, we identify robust and best-suited urban development locations as well as temporal prioritization schemes evolving around future public transportation nodes.