Task Scheduling Strategy for 3DPCP Considering Multidynamic Information Perturbation in Green Scene Article Swipe

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YOU? · · 2024 · Open Access · · DOI: https://doi.org/10.4018/jgim.351156

The 3D printing cloud platform (3DPCP) plays a pivotal role in breaking down the information silos between supply and demand, effectively reducing waste through information integration and intelligent production. However, due to the complexity of 3DPCP scheduling in green scenes and the multidynamic information perturbations, unveils problems in traditional task scheduling methods in 3DPCP. These issues manifest as incomplete considerations, subpar green performance, and weak adaptability to dynamic changes. There is an urgent need to design practical methods to realize the multidynamic information perturbations in green scenes within 3DPCP. Therefore, this article first defines the 3DPCP task scheduling problem for multidynamic information perturbation in green scenes. Second, the article proposes a task scheduling model and a heuristic task scheduling strategy to minimize both the average cost and carbon dioxide (CO2) emissions per unit of quality product. Finally, the article validates effectiveness and superiority of the proposed strategy through simulation experiments.

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Computer Science

Industrial Engineering

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Computer science Scheduling (production processes) Adaptability Dynamic priority scheduling Industrial engineering Two-level scheduling Perturbation (astronomy) Job shop scheduling Operations research Mathematical optimization Distributed computing Real-time computing Schedule Mathematics Engineering Economics Operating system Quantum mechanics Physics Management

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Type: article
Language: en
Landing Page: https://doi.org/10.4018/jgim.351156
PDF: https://www.igi-global.com/ViewTitle.aspx?TitleId=351156&isxn=9798369324523
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Cited By: 2
References: 53
Related Works: 10
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DOI: https://doi.org/10.4018/jgim.351156

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Title: Task Scheduling Strategy for 3DPCP Considering Multidynamic Information Perturbation in Green Scene

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Type: article

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Language: en

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Publication year: 2024

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Publication date: 2024-08-09

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Authors: Jianjia He, Jian Wu, Keng Siau

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Landing page: https://doi.org/10.4018/jgim.351156

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Concepts: Computer science, Scheduling (production processes), Adaptability, Dynamic priority scheduling, Industrial engineering, Two-level scheduling, Perturbation (astronomy), Job shop scheduling, Operations research, Mathematical optimization, Distributed computing, Real-time computing, Schedule, Mathematics, Engineering, Economics, Operating system, Quantum mechanics, Physics, Management

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Cited by: 2

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Citations by year (recent): 2025: 1, 2024: 1

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