Abstract
Humanitarian demining is the process of removing landmines from contaminated areas. Behind this arduous task lies a high risk of collateral damage to deminers and their equipment. The intrinsic operational cost often forces agents to abandon the task before its completion, making such areas a source of risk, especially for the civilian population and biodiversity. Most of the research to date has revolved around the technological development of devices capable of effectively detecting mines at a selected point within an area, while the search strategy itself to decide where to explore and which route to follow has been understudied. This paper proposes a decision support model (DSM) that produces highly safe and cost-effective mine detection search plans. Since the computational time of the solution increases along with the size of the area explored, exact linear methods are proposed for small and medium instances of the problem, whereas a genetic algorithm (GA) is proposed for large instances. Results show that the GA approach is capable of delivering solutions close to the optimum.
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