Computing Maximum Polygonal Packings in Convex Polygons Using Best-Fit, Genetic Algorithms and ILPs (CG Challenge)
A Atak, K Buchin, M Hagedoorn… - 40th International …, 2024 - drops.dagstuhl.de
40th International Symposium on Computational Geometry (SoCG 2024), 2024•drops.dagstuhl.de
Given a convex region P and a set of irregular polygons with associated profits, the
Maximum Polygon Packing Problem seeks a non-overlapping packing of a subset of the
polygons (without rotations) into P maximizing the profit of the packed polygons. Depending
on the size of an instance, we use different algorithmic solutions: integer linear programs for
small instances, genetic algorithms for medium-sized instances and a best-fit approach for
large instances. For packing rectilinear polygons we provide a dedicated best-fit algorithm.
Maximum Polygon Packing Problem seeks a non-overlapping packing of a subset of the
polygons (without rotations) into P maximizing the profit of the packed polygons. Depending
on the size of an instance, we use different algorithmic solutions: integer linear programs for
small instances, genetic algorithms for medium-sized instances and a best-fit approach for
large instances. For packing rectilinear polygons we provide a dedicated best-fit algorithm.
Abstract
Given a convex region P and a set of irregular polygons with associated profits, the Maximum Polygon Packing Problem seeks a non-overlapping packing of a subset of the polygons (without rotations) into P maximizing the profit of the packed polygons. Depending on the size of an instance, we use different algorithmic solutions: integer linear programs for small instances, genetic algorithms for medium-sized instances and a best-fit approach for large instances. For packing rectilinear polygons we provide a dedicated best-fit algorithm.
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