Network-Aware Smart Scheduling for Semi-Automated Ceramic Production via Improved Discrete Hippopotamus Optimization
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| Publicado en: | Electronics vol. 14, no. 17 (2025), p. 3543-3573 |
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| Autor principal: | |
| Otros Autores: | , , , , , , |
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MDPI AG
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| Acceso en línea: | Citation/Abstract Full Text + Graphics Full Text - PDF |
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| 022 | |a 2079-9292 | ||
| 024 | 7 | |a 10.3390/electronics14173543 |2 doi | |
| 035 | |a 3249684653 | ||
| 045 | 2 | |b d20250101 |b d20251231 | |
| 084 | |a 231458 |2 nlm | ||
| 100 | 1 | |a Zhang, Qi |u College of Information Engineering, Shenyang University of Chemical Technology, Shenyang 110142, China; qizhang@syuct.edu.cn (Q.Z.); zhangchangtian194@gmail.com (C.Z.) | |
| 245 | 1 | |a Network-Aware Smart Scheduling for Semi-Automated Ceramic Production via Improved Discrete Hippopotamus Optimization | |
| 260 | |b MDPI AG |c 2025 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a The increasing integration of automation and intelligent sensing technologies in daily-use ceramic manufacturing poses new challenges for efficient scheduling under hybrid flow-shop and shared-kiln constraints. To address these challenges, this study proposes a Mixed-Integer Linear Programming (MILP) model and an Improved Discrete Hippopotamus Optimization (IDHO) algorithm designed for smart, network-aware production environments. The MILP formulation captures key practical features such as batch processing, no-idle kiln constraints, and machine re-entry dynamics. The IDHO algorithm enhances global search performance via segment-based encoding, nonlinear population reduction, and operation-specific mutation strategies, while a parallel evaluation framework accelerates computational efficiency, making the solution viable for industrial-scale, time-sensitive scenarios. The experimental results from 12 benchmark cases demonstrate that IDHO achieves superior performance over six representative metaheuristics (e.g., PSO, GWO, Jaya, DBO), with an average ARPD of 1.04%, statistically significant improvements (p < 0.05), and large effect sizes (Cohen’s d > 0.8). Compared to the commercial solver CPLEX, IDHO provides near-optimal results with substantially lower runtime. The proposed approach contributes to the development of intelligent networked scheduling systems for cyber-physical manufacturing environments, enabling responsive, scalable, and data-driven optimization in smart sensing-enabled production settings. | |
| 651 | 4 | |a China | |
| 653 | |a Linear programming | ||
| 653 | |a Integer programming | ||
| 653 | |a Decision making | ||
| 653 | |a Production scheduling | ||
| 653 | |a Kilns | ||
| 653 | |a Optimization | ||
| 653 | |a Algorithms | ||
| 653 | |a Mixed integer | ||
| 653 | |a Automation | ||
| 653 | |a Manufacturing | ||
| 653 | |a Constraints | ||
| 653 | |a Heuristic methods | ||
| 653 | |a Batch processing | ||
| 700 | 1 | |a Zhang Changtian |u College of Information Engineering, Shenyang University of Chemical Technology, Shenyang 110142, China; qizhang@syuct.edu.cn (Q.Z.); zhangchangtian194@gmail.com (C.Z.) | |
| 700 | 1 | |a Yao, Man |u School of Basic Medicine, He University, Shenyang 110163, China; yaoman@huh.edu.cn | |
| 700 | 1 | |a Guo Xiwang |u College of Information and Control Engineering, Liaoning Petrochemical University, Fushun 113001, China; guoxiwang@lnpu.edu.cn | |
| 700 | 1 | |a Qin Shujin |u School of Information and Technology, Shangqiu Normal University, Shangqiu 476000, China; qinshujin@sqnu.edu.cn | |
| 700 | 1 | |a Zhu, Haibin |u Department of Computer Science and Mathematics, Nipissing University, North Bay, ON P1B 8L7, Canada; haibinz@nipissingu.ca | |
| 700 | 1 | |a Liang, Qi |u Department of Computer Science and Technology, Shandong University of Science and Technology, Qingdao 266590, China | |
| 700 | 1 | |a Hu, Bin |u Department of Computer Science and Technology, Kean University, Union, NJ 07083, USA | |
| 773 | 0 | |t Electronics |g vol. 14, no. 17 (2025), p. 3543-3573 | |
| 786 | 0 | |d ProQuest |t Advanced Technologies & Aerospace Database | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3249684653/abstract/embedded/CH9WPLCLQHQD1J4S?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text + Graphics |u https://www.proquest.com/docview/3249684653/fulltextwithgraphics/embedded/CH9WPLCLQHQD1J4S?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3249684653/fulltextPDF/embedded/CH9WPLCLQHQD1J4S?source=fedsrch |