Isoperimetric Control of an Expanding Set

Consider a contaminated region in a 2-dimensional plane that is expanding with unit normal speed. Our goal is to apply a control function (e.g. pesticide) along the boundary of this region to reduce the contaminated area to zero in the shortest possible time, while consistently clearing a fixed amount of land per unit time. It has been proven that when the initial contamination forms a convex set, an optimal eradication strategy requires applying pesticide to the boundary segments with the highest curvature at each moment. This is equivalent to adopting a myopic strategy that minimizes the perimeter of the contaminated region at each time step. This result provided insight for developing numerical methods to compute approximations of these optimal strategies for convex sets. Namely, our simulation consists in alternating between computing the isoperimetric (perimeter-minimizing) profile with a convex constraint and then dilating the resulting set by a radius equal to the time mesh. This process is repeated until the shape reaches a circle, which can then be trivially scaled down to a point. The isoperimetric profile is obtained through morphological opening, an erosion-dilation operator commonly used in image processing for noise removal. A major open problem remains: a full characterization of optimal eradication strategies for initial contaminations of general shapes. We have applied the above numerical scheme with non-convex constraints to gain some intuition in this broader context. This may entail replacing the morphological opening operator with a more general algorithm relying on the medial axis of a shape. It turns out that, in some configurations, it is more effective to split the contamination into several components and shrink them separately.

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Publication Details

Journal
Inquiry Queen s Undergraduate Research Conference Proceedings
Published
2024-09-09
DOI
https://doi.org/10.24908/iqurcp17986
Primary Topic
Optimization and Variational Analysis
Type
article
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article

Isoperimetric Control of an Expanding Set

Don Kim
Inquiry Queen s Undergraduate Research Conference Proceedings
Optimization and Variational Analysis
article

Isoperimetric Control of an Expanding Set

Don Kim
article en

Abstract

Consider a contaminated region in a 2-dimensional plane that is expanding with unit normal speed. Our goal is to apply a control function (e.g. pesticide) along the boundary of this region to reduce the contaminated area to zero in the shortest possible time, while consistently clearing a fixed amount of land per unit time. It has been proven that when the initial contamination forms a convex set, an optimal eradication strategy requires applying pesticide to the boundary segments with the highest curvature at each moment. This is equivalent to adopting a myopic strategy that minimizes the perimeter of the contaminated region at each time step. This result provided insight for developing numerical methods to compute approximations of these optimal strategies for convex sets. Namely, our simulation consists in alternating between computing the isoperimetric (perimeter-minimizing) profile with a convex constraint and then dilating the resulting set by a radius equal to the time mesh. This process is repeated until the shape reaches a circle, which can then be trivially scaled down to a point. The isoperimetric profile is obtained through morphological opening, an erosion-dilation operator commonly used in image processing for noise removal. A major open problem remains: a full characterization of optimal eradication strategies for initial contaminations of general shapes. We have applied the above numerical scheme with non-convex constraints to gain some intuition in this broader context. This may entail replacing the morphological opening operator with a more general algorithm relying on the medial axis of a shape. It turns out that, in some configurations, it is more effective to split the contamination into several components and shrink them separately.

Inquiry Queen s Undergraduate Research Conference ProceedingsVol. 18(2)
Queen's University (CA)
Openalex Percentile: Top 77%
Optimization and Variational Analysis
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