Home // International Journal On Advances in Software, volume 15, numbers 3 and 4, 2022 // View article

Optimizing Remediation of Spatially Dispersed Contaminated Parcels under an Annual Budget Constraint

Authors:
Floris Abrams
Lieve Sweeck
Johan Camps
Dirk Cattrysse
Jos Van Orshoven

Keywords: Spatio-temporal clustering; Budget constraint; Disaster management; Multi-Attribute Decision Making; MADM.

Abstract:
In environmental disaster management, due to the large impacted area or limited availability of labor and financial resources, setting priorities of where, how and when to act are indispensable. When prioritized interventions on spatially dispersed entities are costly and technically challenging to perform, clustering of individual entities in larger homogeneous actionable units can improve feasibility and reduce cost of the remediation. In this article a spatio-temporal clustering approach under a budget constraint is presented to determine homogenous clusters of polygons and interventions too reduce cost, while still attaining an overall optimal distribution of interventions. We demonstrate the effectiveness of this clustering algorithm with a hypothetical case study, of contaminated agricultural land in Belgium. Finally, we demonstrate the capabilities of the proposed cluster algorithm to provide decision makers with a multi-period action plan reducing the cost of intervention, while still prioritizing resources to the most important sites.

Pages: 188 to 199

Copyright: Copyright (c) to authors, 2022. Used with permission.

Publication date: December 31, 2022

Published in: journal

ISSN: 1942-2628