IEEE Taskforce on Evolutionary Scheduling and Combinatorial Optimisation

IEEE Computational Intelligence Society

Evolutionary Computation Technical Committee



Evolutionary Scheduling and Combinatorial Optimisation Webinar Series



*** Upcoming ***


Webinar #24: Deep Learning Driven Combinatorial Optimization and its Applications

Speaker: Wen Song, Shandong University, China
Date: 17 April 2025
Time: 4:00 - 5:00pm (Beijing Time, UTC+8) [Convert to your local time]
Zoom link: https://vuw.zoom.us/j/95372715200

Speaker Biography

Wen Song received his Bachelor’s and Master’s degrees from Shandong University, China, and the PhD degree from Nanyang Technological University, Singapore. He is currently an Associate Professor with Shandong University, China. His research interests include artificial intelligence, combinatorial optimization, planning and scheduling. His work on learning driven scheduling received the 2024 IEEE TII outstanding paper reward. He served as an Area Chair/Senior PC for top conferences such as ICML, ICLR and AAAI. He is an IEEE Senior Member.

Abstract

Combinatorial optimization is one of the core technologies for intelligent decision-making. Traditional solution algorithms rely on expert experience, often entailing high development costs and relatively poor adaptability. Deep learning driven combinatorial optimization methods, leveraging the powerful representation learning capabilities of deep neural networks, aim to automatically acquire problem-specific knowledge from historical data in a data-driven manner to guide the solution process, offering the potential to overcome the limitations of traditional approaches. This talk will introduce the fundamental principles and main paradigms of this emerging research hotspot, along with the speaker's latest advances in the field and some insights into future directions.


Webinar #25: TBA

Speaker: Ruibin Bai, University of Nottingham Ningbo China
Date: 12 May 2025
Time: 4:00 - 5:00pm (Beijing Time, UTC+8) [Convert to your local time]
Zoom link: TBA

Speaker Biography

TBA

Abstract

TBA


Webinar #26: Large Language Model for Algorithm Design

Speaker: Fei Liu, City University of Hong Kong
Date: 23 June 2025
Time: 4:00 - 5:00pm (Beijing Time, UTC+8) [Convert to your local time]
Zoom link: https://vuw.zoom.us/j/93516613732

Speaker Biography

Fei Liu is a Postdoc in Prof Qingfu Zhang’s group (http://optima.cs.cityu.edu.hk/) at the Department of Computer Science, City University of Hong Kong, Hong Kong. He received his BSc degree and MSc degrees from Northwestern Polytechnical University, China in 2017 and 2020, and Ph.D. degree from City University of Hong Kong, Hong Kong in 2025. His main research interests include computational intelligence, optimization, and their applications. Currently, he is working on Large Language Model for Algorithm Design (LLM4AD). He has published 10+ papers in the journal and conference including TEVC, ICML, KDD, AAAI, IJCAI. He has received Champion of the IEEE HK CI Postgraduate Student Research Paper Competition 2024, Second Price (only one) of the IEEE FLAME Competition 2024, Best Paper Nomination at PPSN 2024, Gold Award in the EMO2021 HUAWEI Logistic Competition, and Outstanding Master's Thesis by CSAA in 2020.

Abstract

Algorithm Design (AD) plays a pivotal role in problem-solving across diverse domains. The emergence of Large Language Models (LLMs) has significantly advanced automation and innovation in this field. We first present a systematic review and taxonomy of the literature on algorithm design utilizing large language models. Next, we introduce Evolution of Heuristic (EoH), an evolutionary framework that integrates LLMs with Evolutionary Computation to facilitate automatic algorithm design. Additionally, we introduce LLM4AD, an open-source, user-friendly platform designed to support algorithm development with large language models. This platform aims to provide modalized tools, methodologies, and tasks, fostering further research and application in the field.


Webinar #27: TBA

Speaker: Yue Xie, University of Cambridge
Date: 28 July 2025
Time: 10:00 - 11:00am (London Time, UTC+1) [Convert to your local time]
Zoom link: TBA

Speaker Biography

TBA

Abstract

TBA


If you have any questions or queries, please email Yi Mei or Fangfang Zhang.




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Past Webinars


  1. Ant Colony Optimization for Complex Routing Problems
    Speaker: Ya-Hui Jia, Assistant Professor, South China University of Technology, China
    Date: 28 April 2022

  2. Evolutionary Neural Architecture Search: Past and Future
    Speaker: Yanan Sun, Professor, Sichuan University, China
    Date: 31 May 2022

  3. 复杂系统智能优化方法及其应用
    Speaker: Xinye Cai, Professor, Dalian University of Technology, China
    Date: 5 July 2022

  4. Automated Algorithm Design - Modelling and Learning on Combinatorial Optimisation Problems
    Speaker: Rong Qu, Associate Professor, University of Nottingham, UK
    Date: 26 July 2022

  5. Evolving Generalizable Solvers for Optimization
    Speaker: Ke Tang, Professor, Southern University of Science and Technology, China
    Date: 3 September 2022

  6. Solution Prediction via Machine Learning for Combinatorial Optimization
    Speaker: Xiaodong Li, Professor, RMIT University, Australia
    Date: 26 October 2022
    Video recording: YouTube and Bilibili.com

  7. Learning to Solve Vehicle Routing Problems
    Speaker: Zhiguang Cao, Scientist, Singapore Institute of Manufacturing Technology (SIMTech), Agency for Science Technology and Research (A*STAR), Singapore
    Date: 9 November 2022

  8. Genetic Programming Hyperheuristics in Dynamic Scheduling
    Speaker: Domagoj Jakobovic, Full Professor, University of Zagreb, Croatia
    Date: 12 January 2023
    Video recording: [YouTube] and [Bilibili.com]

  9. 学习辅助的进化优化算法
    Speaker: Zhi-Hui Zhan, Professor, South China University of Technology, China
    Date: 31 July 2023
    Slides: [PDF]

  10. Combinatorial Optimisation Can be Different from Continuous Optimisation for MOEAs
    Speaker: Miqing Li, Assistant Professor, University of Birmingham, UK
    Date: 31 August 2023
    Video recording: [YouTube]

  11. Why Do We Need Theoretical Research of Evolutionary Algorithms?
    Speaker: Chao Qian, Associate Professor, Nanjing University, China
    Date: 18 September 2023
    Slides: [PDF]

  12. Cross-domain Algorithm Selection: Algorithm Selection across Selection Hyper-heuristics
    Speaker: Mustafa Mısır, Associate Professor, Duke Kunshan University, China
    Date: 26 October 2023
    Video recording: [YouTube]

  13. Unveiling the winning algorithm: A sequence-based selection hyper-heuristic approach to the ROADEF/EURO inventory routing challenge
    Speaker: Ahmed Kheiri, Senior Lecturer, Lancaster University, UK
    Date: 13 May 2024
    Slides: [PDF]

  14. Automated Design of Local Search Algorithms with Machine Learning for Vehicle Routing Problems
    Speaker: Weiyao Meng, Data Scientist (KTP Associate), Nottingham University, UK
    Date: 10 June 2024
    Slides: [PDF]

  15. Collaborative Deep Reinforcement Learning for Solving Multi-Objective Vehicle Routing Problems
    Speaker: Yaoxin Wu, Assistant Professor, Eindhoven University of Technology, The Netherlands
    Date: 8 July 2024
    Video recording: [YouTube]

  16. Meta-Black-Box Optimization: From Automatic Algorithm Configuration to Automatic Algorithm Generation
    Speaker: Yuejiao Gong, South China University of Technology, China
    Date: 16 December 12 August 2024
    Video recording: [YouTube]

    Slides: [PDF]

  17. Evolutionary approaches for drone-assisted electric vehicle routings: effective strategies and lessons learned
    Speaker: Setyo Tri Windras Mara, The University of New South Wales, Australia
    Date: 2 September 2024
    Slides: [PDF]

  18. Neural Combinatorial Optimization with Heavy Decoder: Toward Large Scale Generalization
    Speaker: Zhenkun Wang, Southern University of Science and Technology, China
    Date: 7 October 2024
    Video recording: [YouTube]

    Slides: [PDF]

  19. Automated Design of Selection Hyper-heuristics
    Speaker: Ender Özcan, University of Nottingham, UK
    Date: 4 November 2024
    Video recording: [YouTube]

    Slides: [PDF]

  20. Evolutionary Machine Learning in Business Optimisation
    Speaker: Su Nguyen, RMIT University, Australia
    Date: 2 December 2024
    Video recording: [YouTube]

    Slides: [PDF]

  21. Machine learning for combinatorial optimization and applications
    Speaker: Junchi Yan, Shanghai Jiao Tong University, China
    Date: 13 January 2025
    Slides: [PDF]

  22. Automatically Learn Scheduling Heuristics via Genetic Programming
    Speaker: Meng Xu, A*STAR - Agency for Science, Technology and Research, Singapore
    Date: 17 February 2025
    Video recording: [YouTube]

    Slides: [PDF]

  23. Technology Roadmap for Expensive Combinatorial Optimisation
    Speaker: Handing Wang, Xidian University, China
    Date: 17 March 2025
    Video recording: [YouTube]

    Slides: [PPTX]


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