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🤺 About Me

  He is currently a PhD student at Guangdong University of Technology, focusing on research in evolutionary algorithms, evolutionary multitasking, and vehicle routing problems.

  He is very open to collaborating with potential partners to explore interesting real-world problems.

🔥 News

* Our code is written using open-source tools such as GNU/Octave. 2024-04

* Currently, he is dedicated to researching the use of GNU Octave tool and the writing of basic libraries. He welcomes collaboration with researchers who are passionate about this subject. 2024-04

📃 Recent Work

* Cai Y, Wu Y, Fang C. TSEMTA: A tripartite shared evolutionary multi-task algorithm for optimizing many-task vehicle routing problems[J]. Engineering Applications of Artificial Intelligence, 2024, 133: 108179. paper code password(xliajt8oeMGVo3sb)

* Cai Y, Wu Y, Fang C. Double-assistant evolutionary multitasking algorithm for enhanced electric vehicle routing with backup batteries and battery swapping stations[J]. Expert Systems with Applications, 2024, 237: 121600. paper code password(vzvusSainPHHyutO)

* Zhou X, Wu Y, Peng H, et al. Differential Evolution Algorithm with Dual Information Guidance[J]. International Journal on Artificial Intelligence Tools, 2023, 32(5). paper

* Wu Y, Cai Y, Fang C. Evolutionary multitasking for bidirectional adaptive codec: A case study on vehicle routing problem with time windows[J]. Applied Soft Computing, 2023, 145: 110605. paper

* Zhou X, Wu Y, Wu S, et al. Accelerating artificial bee colony algorithm using elite information[J]. International Journal of Innovative Computing and Applications, 2022, 13(5-6): 325-335. paper

* Zhou X, Wu Y, Zhong M, et al. Artificial bee colony algorithm based on adaptive neighborhood topologies[J]. Information Sciences, 2022, 610: 1078-1101. paper

* Zhou X, Wu Y, Peng H, et al. An individual-dependent differential evolution with dual information guidance[C]//2021 IEEE 33rd International Conference on Tools with Artificial Intelligence (ICTAI). IEEE, 2021: 1170-1177. paper

* Zhou X, Wu Y, Zhong M, et al. Artificial bee colony algorithm based on multiple neighborhood topologies[J]. Applied Soft Computing, 2021, 111: 107697. paper

Yanlin Wu's Projects

awesome-python icon awesome-python

A curated list of awesome Python frameworks, libraries, software and resources

chatgpt icon chatgpt

🔮 ChatGPT Desktop Application (Mac, Windows and Linux)

evrptw_solver icon evrptw_solver

A solver for the electronic vehicle routing problem with time windows

feedback icon feedback

Feedback & wiki for Snipaste https://snipaste.com

gr-based-sapso icon gr-based-sapso

Codebase for the KBS paper: Granularity-based surrogate-assisted particle swarm optimization for high-dimensional expensive optimization

irace-for-matlab icon irace-for-matlab

In this repository, I will include a tutorial for the use of iRace package in the algorithm design in MATLAB.

jmetal icon jmetal

jMetal: a framework for multi-objective optimization with metaheuristics

jsprit icon jsprit

jsprit is a java based, open source toolkit for solving rich vehicle routing problems

l1-ls.py icon l1-ls.py

L1 regularized Least Squares minimization problem solver.

mlofandrew-ng icon mlofandrew-ng

吴恩达机器学习课程的讲义,欢迎大家一起学习

platemo icon platemo

Evolutionary multi-objective optimization platform

rekcarc-tsc-uht icon rekcarc-tsc-uht

清华大学计算机系课程攻略 Guidance for courses in Department of Computer Science and Technology, Tsinghua University

rf-cns icon rf-cns

A random forest assisted evolutionary algorithm using competitive neighborhood search

screentogif icon screentogif

🎬 ScreenToGif allows you to record a selected area of your screen, edit and save it as a gif or video.

sferes2 icon sferes2

A lightweight, generic C++11 framework for evolutionary computation

thu-cst-cracker icon thu-cst-cracker

清华大学计算机系课程攻略 Guidance for courses in Department of Computer Science and Technology, Tsinghua University

tool-tips icon tool-tips

idea 中相见恨晚的技巧 :poop: :poop::poop::poop::poop::poop: 文档访问地址 http://atips.cn/idea/

vrp-rl icon vrp-rl

Reinforcement Learning for Solving the Vehicle Routing Problem

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