Optimizing 3D Irregular Object Packing from 3D Scans Using Metaheuristics. (January 2021)

• Record Type: Journal Article
• Authors: Zhao, Yinghui; Rausch, Chris; Haas, Carl
• Is Part Of: Advanced engineering informatics. Volume 47(2021)
• Publication Date: 2021-01
• Subjects: 3D scanning -- Optimization -- Simulated annealing -- Visual programming -- Meta-heuristics -- 3D irregular packing problems; Computer-aided engineering -- Periodicals; Engineering -- Data processing -- Periodicals; 620.00285
• DOI: 10.1016/j.aei.2020.101234
• Languages: English
• ISSNs: 1474-0346

Abstract

Abstract: 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.