Practical segment intersection with finite precision output
Computational Geometry: Theory and Applications
A Review of the Application ofMeta-Heuristic Algorithms to 2D Strip Packing Problems
Artificial Intelligence Review
Polygon decomposition for efficient construction of Minkowski sums
Computational Geometry: Theory and Applications - Special issue on: Sixteenth European Workshop on Computational Geometry (EUROCG-2000)
Optimization in computer-aided pattern packing (marking, envelopes)
Optimization in computer-aided pattern packing (marking, envelopes)
A comprehensive and robust procedure for obtaining the nofit polygon using Minkowski sums
Computers and Operations Research
Expert Systems with Applications: An International Journal
A beam search implementation for the irregular shape packing problem
Journal of Heuristics
Irregular Packing Using the Line and Arc No-Fit Polygon
Operations Research
Computers and Operations Research
Collision free region determination by modified polygonal Boolean operations
Computer-Aided Design
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The irregular shape packing problem is approached. The container has a fixed width and an open dimension to be minimized. The proposed algorithm constructively creates the solution using an ordered list of items and a placement heuristic. Simulated annealing is the adopted metaheuristic to solve the optimization problem. A two-level algorithm is used to minimize the open dimension of the container. To ensure feasible layouts, the concept of collision free region is used. A collision free region represents all possible translations for an item to be placed and may be degenerated. For a moving item, the proposed placement heuristic detects the presence of exact fits (when the item is fully constrained by its surroundings) and exact slides (when the item position is constrained in all but one direction). The relevance of these positions is analyzed and a new placement heuristic is proposed. Computational comparisons on benchmark problems show that the proposed algorithm generated highly competitive solutions. Moreover, our algorithm updated some best known results.