Portfolio of Solving Strategies in CEGAR-based Object Packing and Scheduling for Sequential 3D Printing
Pavel Surynek

TL;DR
This paper enhances sequential 3D printing object arrangement and scheduling by parallelizing the CEGAR-SEQ algorithm using a portfolio of strategies, leading to more efficient utilization of modern multi-core CPUs and improved performance.
Contribution
It introduces Portfolio-CEGAR-SEQ, a parallelized approach that combines multiple object arrangement strategies to outperform the original CEGAR-SEQ algorithm.
Findings
Portfolio-CEGAR-SEQ outperforms CEGAR-SEQ in experiments.
It often reduces the number of printing plates needed.
Parallelization improves scheduling efficiency.
Abstract
Computing power that used to be available only in supercomputers decades ago especially their parallelism is currently available in standard personal computer CPUs even in CPUs for mobile telephones. We show how to effectively utilize the computing power of modern multi-core personal computer CPU to solve the complex combinatorial problem of object arrangement and scheduling for sequential 3D printing. We achieved this by parallelizing the existing CEGAR-SEQ algorithm that solves the sequential object arrangement and scheduling by expressing it as a linear arithmetic formula which is then solved by a technique inspired by counterexample guided abstraction refinement (CEGAR). The original CEGAR-SEQ algorithm uses an object arrangement strategy that places objects towards the center of the printing plate. We propose alternative object arrangement strategies such as placing objects towards…
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Taxonomy
TopicsOptimization and Packing Problems · VLSI and FPGA Design Techniques · Computational Geometry and Mesh Generation
