A5050605858- Scheduling and Optimization Algorithms
- Advanced Manufacturing and Logistics Optimization
- Assembly Line Balancing Optimization
- Metaheuristic Optimization Algorithms Research
- Advanced Multi-Objective Optimization Algorithms
- Manufacturing Process and Optimization
- Digital Transformation in Industry
- Evolutionary Algorithms and Applications
- Advanced Control Systems Optimization
- Energy Efficiency and Management
- IoT and Edge/Fog Computing
- Optimization and Packing Problems
- Flexible and Reconfigurable Manufacturing Systems
- Elevator Systems and Control
- Collaboration in agile enterprises
- Optimization and Search Problems
- Cloud Computing and Resource Management
- Industrial Vision Systems and Defect Detection
- Smart Grid Energy Management
- Drilling and Well Engineering
- Advanced Algorithms and Applications
- Traffic control and management
- Petri Nets in System Modeling
- Electric Motor Design and Analysis
- Interconnection Networks and Systems
China University of Geosciences
2018-2024
BYD (China)
2024
Tsinghua University
2022
Northeast Forestry University
2022
University of Electronic Science and Technology of China
2021
Beijing Institute of Technology
2018
Huazhong University of Science and Technology
2007-2017
First Automotive Works (China)
2017
Beijing Jiaotong University
2015
Northeastern University
2014
Green flexible job-shop scheduling problem (FJSP) aims to improve profit and reduce energy consumption for modern manufacturing. Meanwhile, FJSP with type-2 fuzzy processing time is proposed predict the uncertainty in timing constraint better simulating practical production. This study addresses multiobjective energy-efficient (ET2FJSP), where minimization of makespan total are considered simultaneously. The previous studies do not propose model verification energy-saving strategy. Moreover,...
Human–robot collaborative scheduling has been widely applied in modern manufacturing industry. A rational of human–robot cooperation plays an important role improving production efficiency. However, problem welding not studied so far. Thus, this article addresses a shop (HCWSSP) with minimization objectives makespan and total energy consumption (TEC). To solve multiobjective HCWSSP, Pareto-based memetic algorithm (PMA), which hybridizes genetic operator variable neighborhood search (VNS), is...
With the development of economy, distributed manufacturing has gradually become mainstream production mode. This work aims to solve energy-efficient flexible job shop scheduling problem (EDFJSP) while simultaneously minimizing makespan and energy consumption. Some gaps are stated following: 1) previous works usually adopt memetic algorithm (MA) with variable neighborhood search. However, local search (LS) operators inefficient due strong randomness; 2) confidence-based adaptive operator...
This study attempts to solve the distributed hybrid flowshop scheduling problem (DHFSP) with makespan criterion. First, a mixed-integer linear programming model for DHFSP is formulated. Then, an improved iterated greedy (IIG) algorithm developed handle this DHFSP. In IIG, new initialization strategy designed improve quality of initial solution. A operator, which combines perturbation operator and destruction/construction proposed enhance global search ability. According characteristics...
Energy-aware distributed heterogeneous flexible job shop scheduling (DHFJS) problem is an extension of the traditional FJS, which harder to solve. This work aims minimize total energy consumption (TEC) and makespan for DHFJS. A deep <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$Q$ </tex-math></inline-formula> -networks-based co-evolution algorithm (DQCE) proposed solve this NP-hard problem, includes four...
Distributed flow shop scheduling of a camshaft machining is an important optimization problem in the automobile industry. The previous studies on distributed mainly emphasized homogeneous factories (shop types are identical from factory to factory) and economic criterion (e.g., makespan tardiness). Nevertheless, heterogeneous varied different factories) environment energy consumption carbon emission) inevitable because requirement practical production life. In this article, we address...
Welding, an irreplaceable process in the modern manufacturing industry, consumes enormous amounts of energy. The schedule a welding shop greatly impacts both its energy consumption and productivity. Thus, it is great significance to solve scheduling problem (WSSP) considering efficiency In this paper, real-life WSSP, multiobjective mathematical model proposed effective artificial bee colony algorithm (MOABC) developed. results designed numerical experiment indicate that MOABC performs better...