A5101848439- Metaheuristic Optimization Algorithms Research
- Evolutionary Algorithms and Applications
- Advanced Multi-Objective Optimization Algorithms
- Artificial Immune Systems Applications
- Cellular Automata and Applications
- Advanced Algorithms and Applications
- Robotic Path Planning Algorithms
- Advanced Manufacturing and Logistics Optimization
- VLSI and FPGA Design Techniques
- Complex Network Analysis Techniques
- Advanced Control Systems Optimization
- Chaos-based Image/Signal Encryption
- Neural Networks and Applications
- Optimization and Packing Problems
- DNA and Biological Computing
- Lattice Boltzmann Simulation Studies
- Reinforcement Learning in Robotics
- Advanced Computational Techniques and Applications
- Vehicle Routing Optimization Methods
- Advanced Image and Video Retrieval Techniques
- Rough Sets and Fuzzy Logic
- Opinion Dynamics and Social Influence
- Scheduling and Optimization Algorithms
- Fluid Dynamics and Turbulent Flows
- Medical Image Segmentation Techniques
Wuhan University
2015-2024
Zhangzhou Normal University
2020-2024
Nanjing University of Information Science and Technology
2024
Iowa State University
2017
State Key Laboratory of Software Engineering
2003-2015
Shanghai Jiao Tong University
2014
Institute of Software
2001-2014
Wuhan University of Technology
2010
In differential evolution algorithm (DE), it is a widely accepted method that selecting individuals with higher fitness to generate mutant vector. this case, the population under fitness-based driving force. Although force beneficial for exploitation, sacrifices performance on exploration. paper, novelty-hybrid-fitness introduced trade off contradictions between exploration and exploitation of DE. new proposed DE, named as NFDDE, both novelty values are considered when choosing create...
In a canonical particle swarm optimization (PSO) algorithm, the fitness is widely accepted criterion when selecting exemplars for particle, which exhibits promising performance in simple unimodal functions. To improve PSO's on complicated multimodal functions, various selection strategies based value are introduced PSO community. However, inherent defects of fitness-based selections still remain. this paper, novelty treated as an additional choosing particle. each generation, few elites and...
Filtering has been an enabling technology and found ever-increasing applications. There are two main classes of digital filters: finite impulse response (FIR) filters infinite (IIR) filters. FIR filter can be guaranteed to have linear phase always stable filters, so is widely applicable. The differential evolution (DE) algorithm, which proposed particularly for numeric optimization problems, a population-based algorithm like the genetic algorithms. In this work, new DE based on reserved...
The Capacitated Arc Routing Problem (CARP) is an essential and challenging problem in smart logistics. Parameter tuning commonly encountered designing applying heuristic or meta-heuristic algorithms for CARP. Recently, automatic parameter hyper-parameter optimization, which focuses on automatically finding optimal setting of algorithm problems at hand, has attracted considerable attention become popular addressing problems. This paper studies advanced solving When CARP, parameters are...
Abstract As a novel swarm intelligence optimization algorithm, cuckoo search (CS) has been successfully applied to solve diverse problems in the real world. Despite its efficiency and wide use, CS some disadvantages, such as premature convergence, easy fall into local optimum poor balance between exploitation exploration. In order improve performance of new extension with multi-swarms Q-Learning namely MP-QL-CS is proposed. The step size strategy algorithm that an individual fitness value...
Discretization of attributes with real values is an important problem in data mining based on rough set. And discretization set has some particular characteristics. The method and Boolean reasoning discussed. Determination of. candidate cuts discussed detail. A theorem proposed. to show that all bound can discern the same objects pairs as whole initial cuts. strategy select proposed theorem. Under strategy, space complexity time improved algorithm decline obviously. experiments results also...
Particle swarm optimization (PSO), differential evolu- tion (DE) and multi-parents crossover (MPC) are the evo- lutionary computation paradigms, all of which have shown superior performance on complex non-linear function op- timization problems. This paper detects underlying re- lationship between them then qualitatively proves that these heuristic approaches from different theoretical prin- ciples consistent in form. Comparison experiments in- volving eight test functions well studied...
One of the main unsolved problems in computer algebra is to determine minimal number multiplications which necessary compute product two matrices. For practical value, small format special interest. This leads a combinatorial optimization problem unlikely solved polynomial time. In this paper, we present method called combining Gaussian eliminations reduce variables and use heuristic ant colony algorithm solve problem. The results experiments on 2 × case show that our achieves significant...
<abstract><p>Opposition-based learning (OBL) is an optimization method widely applied to algorithms. Through analysis, it has been found that different variants of OBL demonstrate varying performance in solving problems, which makes crucial for multiple strategies co-optimize. Therefore, this study proposed a dynamic allocation differential evolution multi-role individuals. Before the population update DAODE, individuals played roles and were stored corresponding archives....