A5101643996- Vehicle Routing Optimization Methods
- Advanced Multi-Objective Optimization Algorithms
- Metaheuristic Optimization Algorithms Research
- Evolutionary Algorithms and Applications
- Optimization and Packing Problems
- Advanced Manufacturing and Logistics Optimization
- Nonlinear Photonic Systems
- Nonlinear Waves and Solitons
- Transportation Planning and Optimization
- Artificial Intelligence in Games
- Facility Location and Emergency Management
- Reinforcement Learning in Robotics
- Maritime Ports and Logistics
- Advanced Mathematical Physics Problems
- Turbomachinery Performance and Optimization
- Manufacturing Process and Optimization
- Advanced Bandit Algorithms Research
- Hand Gesture Recognition Systems
- Traffic Prediction and Management Techniques
- Nuclear Engineering Thermal-Hydraulics
- Advanced Computing and Algorithms
- Genetics, Bioinformatics, and Biomedical Research
- Wireless Signal Modulation Classification
- Scientific Computing and Data Management
- Copper Interconnects and Reliability
Jinan University
2023-2025
Southern University of Science and Technology
2019-2024
University of Birmingham
2020-2024
Kunming University of Science and Technology
2023-2024
University of Science and Technology of China
1993
Surrogate-assisted evolutionary algorithms (SAEAs), which use efficient surrogate models or meta-models to approximate the fitness function in (EAs), are effective and popular methods for solving computationally expensive optimization problems. During past decades, a number of SAEAs have been proposed by combining different EAs. This paper dedicates providing more systematical review comprehensive empirical study used single-objective SAEAs. A new taxonomy is introduced this paper. Surrogate...
In the pursuit of sustainable energy, lithium-ion batteries (LIBs) have revolutionized storage solutions and advanced development electric vehicles. However, as LIBs near their energy density limits face...
Very expensive problems are very common in practical system that one fitness evaluation costs several hours or even days. Surrogate assisted evolutionary algorithms (SAEAs) have been widely used to solve this crucial problem the past decades. However, most studied SAEAs focus on solving with a budget of at least ten times dimension which is unacceptable many real-world problems. In paper, we employ Voronoi diagram boost performance and propose novel framework named Voronoi-based efficient...
The capacitated arc routing problem (CARP) is a challenging combinatorial optimisation abstracted from many real-world applications, such as waste collection, road gritting and mail delivery. However, few studies considered dynamic changes during the vehicles' service, which can cause original schedule infeasible or obsolete. existing are limited by scenarios considered, overly complicated algorithms that unable to benefit wealth of contributions provided CARP literature. In this paper, we...
The static capacitated arc routing problem (CARP) is a challenging combinatorial problem, where vehicles need to be scheduled efficiently for serving set of tasks with minimal travelling costs. Dynamic CARP (DCARP) considers the occurence dynamic events during service process, e.g. traffic congestion, which reduce quality currently applied schedule. Existing research mainly focused on scenarios large changes but neglected time limitations rescheduling process. In this paper, we investigate...
Abstract Engine calibration aims at simultaneously adjusting a set of parameters to ensure the performance an engine under various working conditions using simulator. Due large number be calibrated, measurements considered, and tested, process is very time-consuming relies on human knowledge. In this paper, we consider non-convex constrained search space model real aero-engine problem as many-objective optimisation problem. A fast evolutionary algorithm with shift-based density estimation,...
For solving combinatorial optimisation problems with metaheuristics, different search operators are applied for sampling new solutions in the neighbourhood of a given solution. It is important to understand relationship between various purposes, e.g., adaptively deciding when use which operator find optimal efficiently. However, it difficult theoretically analyse this relationship, especially complex solution space problems. In paper, we propose empirically terms correlation their local...
Reinforcement learning algorithms have performed well in playing challenging board and video games. More more studies focus on improving the generalisation ability of reinforcement algorithms. The General Video Game AI Learning Competition aims to develop agents capable play different game levels that were unseen during training. This paper summarises five years' editions. At each edition, three new games designed. training test designed separately first Since 2020, generated by perturbing...
Abstract Overlapping radio signals recognition is attracting more attention as the development and ubiquitous application of technologies. The traditional blind signal separation (BSS) method mostly not effective when both propagation effects low signal‐to‐noise ratio (SNR) scenarios are taken into consideration. In this letter, joint conformer CNN model (JCCM) proposed to separate recognize overlapping which also unknown by monitor node. JCCM utilizes mechanism encode spectrum feature maps...
Surrogate-assisted evolutionary algorithms (SAEAs) are powerful optimisation tools for computationally expensive problems (CEPs). However, a randomly selected algorithm may fail in solving unknown due to no free lunch theorems, and it will cause more computational resource if we re-run the or try other get much solution, which is serious CEPs. In this paper, consider an portfolio SAEAs reduce risk of choosing inappropriate We propose two frameworks very maximal number fitness evaluations...
The Capacitated Arc Routing Problem (CARP) aims at assigning vehicles to serve tasks which are located different arcs in a graph. However, the originally planned routes easily affected by dynamic events like newly added tasks. This gives rise Dynamic CARP (DCARP) instances, need be efficiently optimized for new high-quality service plans short time. it is unknown make DCARP instances especially hard solve. Therefore, this paper, we provide an investigation of influence on from perspective...
The capacitated arc routing problem (CARP) aims at scheduling a fleet of vehicles with limited capacities to serve set tasks in graph. dynamic CARP (DCARP) optimization focuses on updating the vehicles' service routes when unpredicted events happen and deteriorate current plan. Due outside are still being their located different positions graph remaining capacities, algorithms for static unsuitable solving DCARP instance. However, existing literature, almost all proposed were designed only...
In this paper, we mainly devote to investigate the classification of traveling waves generalized Camassa–Holm equation with dual-power nonlinearities. Utilizing celebrated approach wave solution which was proposed by Jonatan Lenells [Traveling solutions Camassa-Holm equation. J Diff Equ. 2005;217(2):393–430]. We show a result concerns regularity and then classify all solutions.
In this paper, we investigate the existence and stability of solitary waves to rotation–Camassa–Holm equation which can be considered as a model in shallow water for long‐crested propagating near equator with effect Coriolis force due Earth's rotation. We prove by performing phase plane analysis. Moreover, utilizing approach proposed Grillakis–Shatah–Strauss, waves.
Since language models (LMs) now outperform average humans on many challenging tasks, it has become increasingly difficult to develop challenging, high-quality, and realistic evaluations. We address this issue by examining LMs' capabilities generate code for solving real scientific research problems. Incorporating input from scientists AI researchers in 16 diverse natural science sub-fields, including mathematics, physics, chemistry, biology, materials science, we created a scientist-curated...
The dynamic capacitated arc routing problem (DCARP) aims at re-scheduling the service plans of agents, such as vehicles in a city scenario, when events deteriorate quality current schedule. Various algorithms have been proposed to solve DCARP instances different scenarios. However, most existing work evaluated their algorithms' performance based on artificially constructed environments instead using more realistic traffic simulations which are built actual data. In this paper, we novel...
Very expensive problems are very common in practical system that one fitness evaluation costs several hours or even days. Surrogate assisted evolutionary algorithms (SAEAs) have been widely used to solve this crucial problem the past decades. However, most studied SAEAs focus on solving with a budget of at least ten times dimension which is unacceptable many real-world problems. In paper, we employ Voronoi diagram boost performance and propose novel framework named Voronoi-based efficient...