Article
Management
Karim Tamssaouet, Stephane Dauzere-Peres
Summary: This article presents a framework that unifies and generalizes well-known literature results on local search for job-shop and flexible job-shop scheduling problems. The proposed framework focuses on quickly ruling out infeasible moves and evaluating the quality of feasible neighbors, which are crucial for the success of local search approaches. It can be applied to any scheduling problem with an appropriate defined neighborhood structure. The proposed framework introduces novel procedures for evaluating feasibility and estimating the value of objective functions for neighbor solutions.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2023)
Article
Engineering, Industrial
Andy Ham
Summary: This study introduces a novel constraint programming method for simultaneous scheduling of production and material transfer, outperforming traditional benchmark methods. It also proposes a medium-scale benchmark instance for further research and testing.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2021)
Article
Mathematics, Applied
Hernan Diaz, Juan Jose Palacios, Irene Diaz, Camino R. Vela, Ines Gonzalez-Rodriguez
Summary: This paper discusses a variant of the job shop scheduling problem that deals with uncertainty in task durations and due dates using interval modeling. Different ranking methods for intervals are explored and integrated into a genetic algorithm. A new measure of robustness is proposed to evaluate the ability of ranking methods to predict expected delays. Experimental results demonstrate that considering uncertainty during optimization leads to more robust solutions. Sensitivity analysis also indicates that the robustness of solutions improves as uncertainty increases.
LOGIC JOURNAL OF THE IGPL
(2023)
Article
Management
Idir Hamaz, Laurent Houssin, Sonia Cafieri
Summary: This paper addresses the cyclic job shop problem with uncertain task durations in a polyhedral uncertainty set. A two-stage robust optimization model is formulated, and a branch-and-bound algorithm is proposed to minimize the cycle time. Encouraging preliminary results are presented from numerical experiments.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Mathematics
Bowen Zhou, Zhibo Zhang, Chao Xi, Boyu Liu
Summary: This paper proposes a novel two-stage, dual-layer distributed optimization operational approach for microgrids with EVs, which ensures consistent charging/discharging and SOC control of EVs through the lower distributed control layer and determines the optimal operational strategy of the microgrid through the upper optimization scheduling layer.
Article
Computer Science, Artificial Intelligence
Mehmet Akif Sahman
Summary: Scheduling is crucial for manufacturing companies, with job shop scheduling aiming to optimize the sequence of jobs on machines to minimize production time. The distributed job shop scheduling problem (DJSP) becomes more complex with globalization, requiring exact or heuristic solvers. The DSHO algorithm proposed in this study shows promising results as a pioneer solver for DJSP.
APPLIED SOFT COMPUTING
(2021)
Article
Management
Willian T. Lunardi, Ernesto G. Birgin, Debora P. Ronconi, Holger Voos
Summary: This work investigates the online printing shop scheduling problem, proposing a local search strategy and metaheuristics which have been shown through extensive numerical experiments to be suitable for solving practical instances and competitive in classical instances of the problem.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2021)
Article
Mathematics
Sandor Szabo, Bogdan Zavalnij
Summary: This paper focuses on a special clique search problem, which aims to find a clique with k nodes in a given k-partite graph. The paper proposes kernelization methods tailored to this specific problem and shows their efficiency through numerical experiments. The paper also highlights the importance of preconditioning or kernelization in large scale clique search and demonstrates the potential practical utility of the restricted type clique search problem in solving non-trivial scheduling problems.
Article
Computer Science, Artificial Intelligence
Fangfang Zhang, Yi Mei, Su Nguyen, Mengjie Zhang, Kay Chen Tan
Summary: This paper proposes a novel surrogate-assisted evolutionary multitask algorithm via GP to share useful knowledge between different scheduling tasks to improve training efficiency and effectiveness. Phenotypic characterization is used to measure the behaviors of scheduling rules and build a surrogate for each task. The proposed algorithm successfully improves the quality of scheduling heuristics for all scenarios.
IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION
(2021)
Article
Management
Krzysztof Kurowski, Tomasz Pecyna, Mateusz Slysz, Rafal Rozycki, Grzegorz Waligora, Jan Weglarz
Summary: The Job Shop Scheduling Problem (JSSP) is a complex and industry essential scheduling problem. Traditional algorithms for optimizing the makespan of a given schedule are limited by computational power. Inspired by the use of Quantum Annealing (QA), we propose a new approach using gate-model quantum architecture to solve JSSP instances. We demonstrate the effectiveness of Quantum Approximate Optimization Algorithm (QAOA) in solving JSSP and analyze its performance with varying parameters.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2023)
Article
Engineering, Electrical & Electronic
Leonilde R. Varela, Catia F. V. Alves, Andre S. Santos, Gaspar G. Vieira, Nuno Lopes, Goran D. Putnik
Summary: Collaborative Manufacturing Scheduling (CMS) is a potential but not yet fully explored decision making practice in the digital era. This paper proposes an interoperable scheduling system and analyzes it through an industrial case study. The results suggest that the weighted application scenario can achieve a more balanced and attractive global solution when considering different performance measures.
Article
Computer Science, Information Systems
Yuling He, Xuewei Wu, Kai Sun, Xiaodong Du, Haipeng Wang, Jianli Zhao
Summary: In this paper, an economic scheduling model considering the load demand for a microgrid system under the mechanism of a peak-valley tariff is proposed. The exchange power between the microgrid and main network is determined using a mathematical model of the microgrid components. An improved War Strategy Optimization (WSO) algorithm is used to investigate different scenarios, and the results show that the improved WSO algorithm performs better in optimizing the proposed scheduling model.
Article
Automation & Control Systems
Raul Mencia, Carlos Mencia, Ramiro Varela
Summary: We address the task of repairing infeasibility in job shop scheduling problems with a hard constraint on the maximum makespan. By adopting a job-based view of repairs and proposing enhancements to a genetic algorithm, we aim to improve efficiency and effectiveness in solving the problem. The proposed methods show significant improvements in experimental results.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2021)
Article
Management
Karim Tamssaouet, Stephane Dauzere-Peres, Sebastian Knopp, Abdoul Bitar, Claude Yugma
Summary: This paper addresses a multiobjective complex job-shop scheduling problem in semiconductor manufacturing by extending a batch-oblivious approach, introducing a criterion for production target satisfaction and a preference model. The proposed approach provides good solutions and significant improvements compared to actual factory schedules.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2022)
Article
Computer Science, Interdisciplinary Applications
Xixing Li, Xing Guo, Hongtao Tang, Rui Wu, Lei Wang, Shibao Pang, Zhengchao Liu, Wenxiang Xu, Xin Li
Summary: This paper presents a comprehensive literature review on the integrated optimization of the flexible job shop scheduling problem (FJSP). Five different integration models of FJSP are explained and research challenges and directions are demonstrated. The study aims to aid academic researchers and application engineers in Industry 4.0.
COMPUTERS & INDUSTRIAL ENGINEERING
(2022)
Article
Automation & Control Systems
Yu Jin, Qian Xiao, Hongjie Jia, Yanchao Ji, Tomislav Dragicevic, Remus Teodorescu, Frede Blaabjerg
Summary: This article proposes a simplified and fast software-based fault detection and localization approach for the grid-connected modular multilevel converter. By calculating and comparing the errors between measured and estimated state variables, switch faults can be detected and localized. A modified Pauta criterion is used to confirm the faults. Simulation and experimental results demonstrate the effectiveness of the proposed approach.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2023)
Article
Automation & Control Systems
Qian Xiao, Shunfeng Yang, Yu Jin, Hongjie Jia, Josep Pou, Remus Teodorescu, Frede Blaabjerg
Summary: This article proposes a decoupled control scheme for the modular multilevel converter (MMC) to reduce the total harmonic distortion (THD) and eliminate one specific harmonic. By using an improved nearest level control method, a staircase wave is generated and one specific harmonic can be eliminated by adding additional pulses. A decoupled circulating current fuzzy control method is also introduced to suppress the second-order harmonic and balance the energy.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2023)
Review
Energy & Fuels
Mobin Naderi, Yousef Khayat, Qobad Shafiee, Frede Blaabjerg, Hassan Bevrani
Summary: This paper reviews concepts and methods related to interconnected microgrids (IMGs), including modeling, stability analysis, and control. The benefits of interconnecting microgrids are highlighted, such as improved reliability and renewable energy integration. However, maintaining stability and employing suitable control methods are important for maximizing these benefits. The paper provides a comparison of dynamic modeling methods, as well as a review and comparison of stability analysis and control methods for IMGs. The review is supported by diagrams, tables, and simulations using MATLAB and OPAL-RT.
Article
Automation & Control Systems
Chaochao Song, Ariya Sangwongwanich, Yongheng Yang, Frede Blaabjerg
Summary: This article proposes a balancing control scheme based on the complementary switching-state method to address two typical problems in capacitor voltage balancing. The method can significantly reduce power fluctuation and current overshoot during the balancing process, as well as simplify the determination of transformer current polarity.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2023)
Article
Automation & Control Systems
Jianjun Chen, Weihao Hu, Di Cao, Zhenyuan Zhang, Zhe Chen, Frede Blaabjerg
Summary: This article proposes a novel meta-learning-enabled method for effective detection of fault in rolling bearings of electric machines with limited data. The method utilizes a model-agnostic meta-learning-based model to solve the few-shot classification problem of fault diagnosis under various working conditions. The results show that the proposed method outperforms other state-of-the-art methods, achieving high fault-detection accuracy and demonstrating stronger generalization and faster adaptation abilities.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2023)
Article
Engineering, Electrical & Electronic
Zhan Shen, Wu Chen, Hongbo Zhao, Long Jin, Alex J. Hanson, David J. Perreault, Charles R. Sullivan, Frede Blaabjerg, Huai Wang
Summary: NiZn cores are commonly used in the high-frequency range due to their lower permeability and permittivity compared to other materials. Previous capacitance models based on perfect electrical conductor assumption are not applicable for NiZn cores. We propose a general core energy capacitance model obtained by solving the electric field boundary value problem, as well as a simplified model obtained through curve fitting to finite element analysis data. Both models are verified through simulation and experimental results in two case studies with rod and pot core structures.
IEEE TRANSACTIONS ON POWER ELECTRONICS
(2023)
Article
Green & Sustainable Science & Technology
Sijia Li, Arman Oshnoei, Frede Blaabjerg, Amjad Anvari-Moghaddam
Summary: Microgrids enable efficient utilization of integrated energy systems with renewable energy sources. Managing fluctuating renewable energy generation and sudden load changes is a major challenge in microgrid control and operation. Hierarchical control techniques have received attention, with machine learning-based approaches showing promising features and performance. This paper reviews the application of classical control and machine learning techniques in hierarchical control systems, comparing their methods, advantages, disadvantages, and implementation across different control levels. The paper highlights the potential of machine learning to enhance control accuracy and address system optimization concerns in microgrid hierarchical control, but challenges such as computational intensity, stability analysis, and experimental validation remain to be addressed.
Article
Energy & Fuels
Sichen Li, Weihao Hu, Di Cao, Zhe Chen, Qi Huang, Frede Blaabjerg, Kaiji Liao
Summary: This paper proposes a physics-model-free control framework for the energy management of MMGs with heat-electricity energy, using a surrogate model and multi-agent deep reinforcement learning. The proposed approach overcomes the reliance on precise system parameters and demonstrates effectiveness in simulation results.
Article
Engineering, Electrical & Electronic
Arman Oshnoei, Abd Alelah Derbas, Saeed Peyghami, Frede Blaabjerg
Summary: This paper proposes a tube-based FCS-MPC method for controlling the output voltage of a voltage source converter. The method combines two FCS-MPC controllers to weaken the impact of model uncertainties and improve the performance of the controller.
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS
(2023)
Article
Engineering, Electrical & Electronic
Nima Tashakor, Yi Zhang, Shady Banana, Frede Blaabjerg, Stefan Goetz
Summary: This article introduces a sensorless voltage-balancing strategy and a simple controller for modular multilevel converters. By using diodes to provide a unidirectional balancing path, diode-clamped MMCs offer a simple and effective solution. The open-loop operation of the model compensates for the lack of bidirectional energy transfer. While sensorless operation reduces costs, precise knowledge of module voltages still improves operation in certain applications.
IEEE TRANSACTIONS ON POWER ELECTRONICS
(2023)
Article
Engineering, Electrical & Electronic
Zhaoyang Zhao, Haitao Hu, Zhengyou He, Herbert Ho-Ching Iu, Pooya Davari, Frede Blaabjerg
Summary: This article provides an overview of power electronics (PE)-based safety enhancement technologies for lithium-ion batteries (LIBs), especially focusing on battery management. It introduces the latest advances in battery protection, balancing, monitoring, and lifetime improvement, all based on PE technologies. Detailed discussions and future research opportunities are presented. This article aims to serve as a reference for PE researchers interested in improving LIB safety.
IEEE TRANSACTIONS ON POWER ELECTRONICS
(2023)
Article
Engineering, Electrical & Electronic
Bin Hu, Heng Nian, Haipan Li, Liang Chen, Subham Sahoo, Frede Blaabjerg
Summary: This article analyzes the broadband negative resistive characteristic of DFIG-based wind power systems and the resonance risks when connected with weak or diverse grid transmission infrastructure based on passivity-based stability assessment. It identifies the current controller, phase locked loop, and system delay as the dominant factors for the negative resistive region within low frequency, middle frequency, and high frequency, respectively. The article reveals the impedance reshaping band coupling phenomenon and proposes a broadband passivity enhancement method for DFIG systems. Experimental results confirm the conclusions and effectiveness of the proposed method.
IEEE TRANSACTIONS ON POWER ELECTRONICS
(2023)
Article
Engineering, Electrical & Electronic
Sichen Li, Weihao Hu, Di Cao, Sayed Abulanwar, Zhenyuan Zhang, Zhe Chen, Frede Blaabjerg
Summary: This paper proposes a novel multi-agent deep reinforcement learning approach for energy management and voltage control. By utilizing trajectory history information and opponent modeling, it avoids control collapse caused by missing measurements.
IEEE TRANSACTIONS ON SMART GRID
(2023)
Review
Computer Science, Information Systems
Amritansh Sagar, Arun Kashyap, Morteza Azimi Nasab, Sanjeevikumar Padmanaban, Manuele Bertoluzzo, Abhay Kumar, Frede Blaabjerg
Summary: The expanding Electric vehicle (EV) market is driven by the need for more efficient and reliable ways to recharge the battery. The Wireless Power Transfer (WPT) methodology eliminates the drawbacks and risks associated with the conventional conductive system by removing the need for direct physical interaction between vehicles and charge equipment. Various strategies have been developed to enhance the effectiveness and reliability of the WPT model for EV charging.
Review
Computer Science, Information Systems
Pawan Kumar Pathak, Debasmita Ghosh Roy, Anil Kumar Yadav, Sanjeevikumar Padmanaban, Frede Blaabjerg, Baseem Khan
Summary: One critical emerging branch of solar technology is photovoltaic/thermal (PV/T) systems, which combine solar collectors and solar photovoltaic panels into a unit to produce heat and electricity. The conversion efficiency (η) of solar panels is reduced due to the elevated temperature of solar cells, but PV/T systems aim to minimize the temperature and enhance electricity production. This study reviews cooling media, such as air, fluids, and phase change materials, for PV/T systems and provides recommendations for future implementations.
