A5046524792- Advanced Sensor and Control Systems
- Industrial Technology and Control Systems
- Evolutionary Game Theory and Cooperation
- Metaheuristic Optimization Algorithms Research
- Advanced Algorithms and Applications
- Experimental Behavioral Economics Studies
- Advanced Multi-Objective Optimization Algorithms
- Advanced Computational Techniques and Applications
- Service-Oriented Architecture and Web Services
- Evolutionary Algorithms and Applications
- Simulation and Modeling Applications
- Mathematical and Theoretical Epidemiology and Ecology Models
- Embedded Systems and FPGA Design
- Opinion Dynamics and Social Influence
- Evolution and Genetic Dynamics
- Indoor and Outdoor Localization Technologies
- Mobile Agent-Based Network Management
- Power Systems and Technologies
- Industrial Automation and Control Systems
- Robotics and Sensor-Based Localization
- Wireless Sensor Networks and IoT
- Complex Network Analysis Techniques
- Inertial Sensor and Navigation
- Advanced Measurement and Detection Methods
- Collaboration in agile enterprises
Yunnan University
2011-2025
Zhejiang Center for Disease Control and Prevention
2024
Huzhou University
2024
University of Illinois Chicago
2024
Tongji University
2005-2022
Hangzhou Normal University
2021
Jiangsu University of Science and Technology
2008-2020
Yunnan Nationalities University
2008-2018
Shanghai Institute of Measurement and Testing Technology
2016-2018
Shandong University of Technology
2013
For longevity in the market, manufacturers must strike a balance between monetary benefits and production capability. This article investigates distributed hybrid flowshop scheduling problem with deteriorating jobs, objective of minimizing makespan mean tardiness. A mathematical model for is constructed. To minimize goals, multi-objective discrete differential evolution (MODDE) method put forward. achieving optimization two-strategy initialization operation forth. local search strategy...
The behavior of a photovoltaic (PV) system can be derived from its current–voltage characteristics, depending on unknown circuit model parameters. It is significant to accurately and efficiently extract the parameters PV because nonlinear, multivariable, multimodal characteristics. Many meta-heuristic algorithms have been proposed, in which differential evolution (DE) known for simple structure, ease use, fast convergence. However, performance DEs still has room further improvement...
This work effectively modifies APSM-jSO (a novel jSO variant with an adaptive parameter selection mechanism and a new external archive updating mechanism) to offer (single objective real-parameter optimization: Algorithm jSO) version called NLAPSMjSO-EDA. There are three main distinctions between NLAPSMjSO-EDA APSM-jSO. Firstly, in the linear population reduction strategy, number of individuals eliminated each generation is insufficient. results higher inferior remaining, since total...
To cope with common local optimum traps and balance exploration development in complex multi-peak optimisation problems, this paper puts forth a Dual-Performance Multi-subpopulation Adaptive Restart Differential Evolutionary Algorithm (DPR-MGDE) as potential solution. The algorithm employs novel approach by utilising the fitness historical update frequency dual-performance metrics to categorise population into three distinct sub-populations: PM (the promising individual set), MM medium set)...
Low carbon manufacturing has received increasingly more attention in the context of global warming. The flexible job shop scheduling problem (FJSP) widely exists various processes. Researchers have always emphasized efficiency and economic benefits while ignoring environmental impacts. In this paper, considering emissions, a multi-objective (MO-FJSP) mathematical model with minimum completion time, emission, machine load is established. To solve problem, we study six variants non-dominated...
Particle swarm optimization (PSO) is an algorithm widely used to solve problems. Multi-swarm particle (MSPSO) a form of (PSO). The size the multi-swarm important characteristic algorithm. number particles and swarms will affect performance varying degrees. studied from perspective size.
Swarm-based algorithm can successfully avoid the local optimal constraints, thus achieving a smooth balance between exploration and exploitation. Salp swarm (SSA), as swarm-based on account of predation behavior salp, solve complex daily life optimization problems in nature. SSA also has stagnation slow convergence rate. This paper introduces an improved salp algorithm, which improve by using chaotic sequence initialization strategy symmetric adaptive population division. Moreover, simulated...
One of the limitations dung beetle optimization (DBO) is its susceptibility to local optima and relatively low search accuracy. Several strategies have been utilized improve diversity, precision, outcomes DBO. However, equilibrium between exploration exploitation has not achieved optimally. This paper presents a novel algorithm called ODBO, which incorporates cat map an opposition-based learning strategy, based on symmetry theory. In addition, in order enhance performance ball rolling phase,...
Proposing new strategies to improve the optimization performance of differential evolution (DE) is an important research study. The jSO algorithm was announced winner Congress on Evolutionary Computation (CEC) 2017 competition numerical optimization, and state-of-the-art in SHADE (Success-History based Adaptive Differential Evolution) series. However, converges prematurely search space with different dimensions prone falling into local optimum during evolution, as well problem decreasing...
Evolutionary Algorithms (EAs) based Unmanned Aerial Vehicle (UAV) path planners have been extensively studied for their effectiveness and high concurrency. However, when there are many obstacles, the can easily violate constraints during evolutionary process. Even if a single waypoint causes few constraint violations, algorithm will discard these solutions. In this paper, planning is constructed as multi-objective optimization problem with in three-dimensional terrain scenario. To solve an...
The collision warning system (CWS) plays an essential role in vehicle active safety. However, traditional distance-measuring solutions, e.g., millimeter-wave radars, ultrasonic and lidars, fail to reflect vehicles’ relative attitude motion trends. In this paper, we proposed a vehicle-to-vehicle (V2V) cooperative (CCWS) consisting of ultra-wideband (UWB) positioning/directing module dead reckoning (DR) with wheel-speed sensors. Each has four UWB modules on the body corners two sensors rear...