IEEE Taskforce on Evolutionary Scheduling and Combinatorial Optimisation

IEEE Computational Intelligence Society

Evolutionary Computation Technical Committee

Welcome

Welcome to the website of the IEEE Taskforce on Evolutionary Scheduling and Combinatorial Optimisation, a taskforce under the Evolutionary Computation Technical Committee, IEEE Computational Intelligence Society. We are passionate to organise events and activities on evolutionary scheduling and combinatorial optimisation, to create opportunities for researchers and industrial practitioners to share ideas, seek for collaborations, and make friends together!

If you are interested in joining this taskforce or receiving updates from us, please feel free to contact Yi Mei.

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Scope and Mission

Scheduling and combinatorial optimisation is an important research area at the interface of artificial intelligence and operations research. It has attracted the attention of researchers over the years due to its wide applicability to the real world and interesting computational aspects.

Evolutionary computation approaches have been successfully applied to solve these problems since they are highly flexible regarding handling constraints, dynamic environment changes, multiple conflicting objectives, and automatic algorithm design/configuration. With the growth of new technologies and business models, researchers in this field are continuously facing new challenges, which requires innovative solution methods.

This scope of this taskforce focuses on both practical and theoretical aspects of Evolutionary Scheduling and Combinatorial Optimisation (ESCO). Examples of evolutionary methods include genetic algorithms, genetic programming, evolutionary strategies, ant colony optimisation, particle swarm optimisation, evolutionary-based hyper-heuristics, and memetic algorithms. We also focus on novel hybrid approaches that combine machine learning and evolutionary computation to solve complex ESCO problems. Examples include using machine learning to improve surrogate-assisted evolutionary algorithms, and designing evolutionary algorithms for reinforcement learning and transfer/multitask learning.

The mission of this taskforce is to organise events and activities (e.g., conference workshops, tutorials, special sessions, competitions, journal special issues), to provide a platform for researchers and industrial practitioners to share ideas, seek for collaborations, and find solutions to their problems. It will serve at least the following groups of people:


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Events and Activities

Tutorial: Evolutionary Computation meets Machine Learning for Combinatorial Optimisation

Yi Mei, Guenther Raidl
ACM Genetic and Evolutionary Computation Conference, 14 - 18 July 2024, Melbourne, Australia.

Tutorial: Explainable Artificial Intelligence by Genetic Programming

Yi Mei, Qi Chen, Andrew Lensen, Bing Xue, Mengjie Zhang
IEEE World Congress on Computational Intelligence, 30 June – 5 July 2024, Yokohama, Japan.

Tutorial: Genetic Programming and Machine Learning for Scheduling

Fangfang Zhang
IEEE World Congress on Computational Intelligence, 30 June – 5 July 2024, Yokohama, Japan.

Special Issue on Advancing Computational Intelligence in Autonomous Learning and Optimization Systems

Yaqing Hou, Liang Feng, Yi Mei
IEEE Computational Intelligence Magazine, 2024.

Special Session on Evolutionary Computation and Computational Intelligence for Scheduling and Combinatorial Optimisation

Yi Mei, Su Nguyen, Aaron Chen, Fangfang Zhang
IEEE World Congress on Computational Intelligence, 30 June – 5 July 2024, Yokohama, Japan.

Special Session on Evolutionary Computation for Electric Vehicle Routing and Charging

Yahui Jia, Qiang Yang, Wei-Neng Chen
IEEE World Congress on Computational Intelligence, 30 June – 5 July 2024, Yokohama, Japan.

IEEE Symposium on Evolutionary Scheduling and Combinatorial Optimisation

Yi Mei, Nelishia Pillay, Liang Gao, Rong Qu
IEEE Symposium Series On Computational Intelligence, 5-8 December, 2023, Mexico City, Mexico.

The Distributed Ghost: Cellular Automata, Distributed Dynamical Systems, and Their Applications to Intelligence

Stefano Nichele, Hiroki Sayama, Chrystopher Nehaniv, Eric Medvet, Mario Pavone
Workshop at ALIFE, 27 July, 2023, Sapporo, Japan.

Special Session on Evolutionary Scheduling and Combinatorial Optimisation

Yi Mei, Su Nguyen, Aaron Chen, Fangfang Zhang
IEEE Congress on Evolutionary Computation, 3-5 July, 2023, Chicago, USA.

Special Session on Genetic Programming and Machine Learning for Scheduling

Fangfang Zhang, Mengjie Zhang, Yi Mei, Su Nguyen
IEEE Congress on Evolutionary Computation, 3-5 July, 2023, Chicago, USA.

Tutorial: Genetic Programming and Machine Learning for Scheduling

Fangfang Zhang
IEEE Congress on Evolutionary Computation, 3-5 July, 2023, Chicago, USA.

Keynote Speech: Human-Computer Intelligence in Combinatorial Problem Solving

Ruhul Sarker
IEEE Symposium Series On Computational Intelligence, Symposium on Evolutionary Scheduling and Combinatorial Optimisation, 4-7 December, 2022, Singapore.

Tutorial: Genetic Programming and Machine Learning for Job Shop Scheduling

Fangfang Zhang
IEEE Symposium Series On Computational Intelligence, 4-7 December, 2022, Singapore.

IEEE Symposium on Evolutionary Scheduling and Combinatorial Optimisation

Yi Mei, Rong Qu, Nelishia Pillay, Liang Gao
IEEE Symposium Series On Computational Intelligence, 4-7 December, 2022, Singapore.

IEEE CIS Live Webinar: Selection Hyper-Heuristics for Automated Design, Configuration and Selection

Rong Qu
Online, 25 May, 2022.

Tutorial: Evolutionary Machine Learning for Combinatorial Optimisation

Fangfang Zhang, Yi Mei, Su Nguyen, Mengjie Zhang
IEEE World Congress on Computational Intelligence, 18-23 July, 2022, Padova, Italy.

Tutorial: Introduction to automated design of scheduling heuristics with genetic programming

‪Domagoj Jakobović‬, Marko Ðurasević, Su Nguyen, Yi Mei, Mengjie Zhang
ACM Genetic and Evolutionary Computation Conference, 9-13 July, 2022, Boston, USA.

Special Session on Evolutionary Scheduling and Combinatorial Optimisation

Yi Mei, Su Nguyen, Aaron Chen, Fangfang Zhang
IEEE World Congress on Computational Intelligence, 18-23 July, 2022, Padova, Italy.

Special Session on Evolutionary Machine Learning for Planning and Scheduling

Fangfang Zhang, Yi Mei, Su Nguyen, Mengjie Zhang
IEEE World Congress on Computational Intelligence, 18-23 July, 2022, Padova, Italy.

IEEE Symposium on Evolutionary Scheduling and Combinatorial Optimisation

Yi Mei, Rong Qu, Nelishia Pillay, Liang Gao
IEEE Symposium Series on Computational Intelligence, 5-7 December, 2021, Orlando, Florida, USA (Virtual).

Keynote Speech: Scheduling Dynamic Job Shops – An Anticipative And A Self-Organization Approach

Juergen Branke
IEEE Symposium Series on Computational Intelligence, 5-7 December, 2021, Orlando, Florida, USA (Virtual).

Tutorial: Genetic Programming for Job Shop Scheduling

Fangfang Zhang, Yi Mei, Su Nguyen, Mengjie Zhang
IEEE Symposium Series on Computational Intelligence, 5-7 December, 2021, Orlando, Florida, USA (Virtual).


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