Advancing multi‐objective optimization in spatial planning

Growing demands for food, energy, minerals and other natural resources are intensifying pressure on ecosystems. Meeting these demands while reducing biodiversity loss requires making decisions about which areas can simultaneously support sustainable development, conserve biodiversity and maintain or restore ecosystem services.

Existing spatial optimization tools in planning contexts offer limited support to accommodate multiple objectives, such as maximizing agricultural production and biodiversity outcomes, because they rely on predefined formulations that lack the flexibility to incorporate objectives from multiple sectors and explicitly characterize trade‐offs and synergies among them.

Here, we present a multi‐objective optimization framework for spatial planning. The framework is used to express multiple planning goals and requirements as optimization problems, identify solutions that simultaneously satisfy multiple objectives and explore trade‐offs between them. It provides a flexible structure for specifying objectives within and across sectors and supports multiple multi‐objective optimization approaches—weighted‐sum, hierarchical and reference point approaches. To promote accessibility, we implemented the framework as an update to the prioritizr R package.

Using a multiple‐use case study in the European Union, we demonstrate how the framework supports the identification of solutions that balance trade‐offs between ecosystem restoration, agriculture and forestry production.

Synthesis and applications. Our framework enables conservation scientists, planners and practitioners to identify spatial plans that achieve multiple objectives. It is designed to help explore trade‐offs across a broad range of domains, including terrestrial, marine and freshwater realms. By reducing technical barriers, the framework facilitates exploration of trade‐offs and identification of co‐benefits across diverse ecological, economic and social planning contexts.