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
Autor principal: Zhang, Qi
Otros Autores: Zhang Changtian, Yao, Man, Guo Xiwang, Qin Shujin, Zhu, Haibin, Liang, Qi, Hu, Bin
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MDPI AG
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024 7 |a 10.3390/electronics14173543  |2 doi 
035 |a 3249684653 
045 2 |b d20250101  |b d20251231 
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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