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Optimizing 3d irregular Object packing from 3d Scans Using Metaheuristics

AdVANCEd ENGINEERING INFORMATICS 2021年 47卷 101234-101234页

作者： Zhao, Yinghui Rausch, Chris Haas, Carl Univ Waterloo Dept Civil & Environm Engn Waterloo ON N2L 3G1 Canada

For efficient construction-assemblies transportation, volume constrained 3d printing, dry stacking, and facility waste management, a common problem must be solved. It is the practical problem of packing irregular 3d rigid objects into a container with fixed dimensions so that the volume of the final packed objects is minimized. To solve this problem, a methodology is presented that begins with capturing the initial as-is 3d shape data for each object, followed by a metaheuristic-based packing optimization algorithm. This methodology is demonstrated to be effective in two situations with known optimum solutions and in a third situation involving packing of real-life as-is objects. A high-level selection algorithm that is designed to guide the search of possible object subsets, when not all objects can fit into a single predefined container, is discussed as well. Performance is examined for variations, and a preliminary sensitivity analysis is performed. The methodology and its key algorithms are demonstrated to produce effective packing solutions in a mostly automatic manner. Object packing for this class of applications in civil engineering can thus be potentially improved in terms of outcome efficiency and level of planning effort required.

关键词： 3d scanning Optimization Simulated annealing Visual programming Meta-heuristics 3d irregular packing problems

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