Opensource spatial optimization in GIScience for strategic positioning

Spatial optimization involving multiple objectives is commonly needed to address complex planning and management issues yet associated models and problems are exceptionally difficult and complicated to solve. Open-source approaches have received attention because they offer potential for making spatial optimization more broadly available, and other GIScience methods, to support analysis and decision-making. Beyond this, the ability to integrate GIScience functions through open-source alternatives offers great potential to decrease reliance on commercial, proprietary software as well as enable broader use and adoption of, and reliance on, spatial optimization approaches. This article details an important bi-objective spatial problem along with open-source capabilities for solution as an example of challenges faced and opportunities possible. A number of solution approaches are considered, providing an opportunity to assess computational requirements, functionality, solution quality and issues encountered. Empirical applications associated with emergency response, healthcare access, food processing and strategic player positioning are detailed. This study highlights capabilities, limitations and challenges for open-source science in addressing a class of multi-objective spatial optimization problems.

Automated summary

Spatial optimization with multiple objectives is complex, and open-source approaches offer potential for wider access and integration of GIScience methods. This article presents a bi-objective spatial problem as an example to illustrate the challenges and opportunities of open-source solutions. It discusses various solution approaches and their computational requirements, functionality, solution quality, and encountered issues. Empirical applications in emergency response, healthcare access, food processing, and strategic player positioning are detailed. This study highlights the capabilities, limitations, and challenges of open-source science in addressing multi-objective spatial optimization problems.