A Collection of Main Papers on Multitasking Optimization
Paper Title
Venue
Year
Authors
Materials
Comment
1. Back to the Roots Multi-X Evolutionary Computation
Cognitive Computation
2019
Gupta et al. [paper ]
2. Evolutionary Multitask Optimization a Methodological Overview Challenges and Future Research Directions
arXiv
2021
Osaba et al. [paper ]
3. Multi-Task Optimization and Multi-Task Evolutionary Computation in the Past Five Years A Brief Review
Mathematics
2021
Xu et al. [paper ]
4. Evolutionary Transfer Optimization A New Frontier in Evolutionary Computation Research
CIM
2021
Tan et al. [paper ]
5. Half a Dozen Real-World Applications of Evolutionary Multitasking and More
CIM
2022
Gupta et al. [paper ]
6. A Review on Evolutionary Multi-Task Optimization: Trends and Challenges
TEVC
2022
Wei et al. [paper ]
7. How to Exploit Optimization Experience? Revisiting Evolutionary Sequential Transfer Optimization: Part A - Benchmark Problems
Techrxiv
2023
Xue et al. [paper ]
8. How to Exploit Optimization Experience? Revisiting Evolutionary Sequential Transfer Optimization: Part B - Algorithm Analysis
Techrxiv
2023
Xue et al. [paper ]
Multitasking Single-objective Optimization
Paper Title
Venue
Year
Authors
Materials
Comment
1. Multifactorial Evolution Toward Evolutionary Multitasking
TEVC
2016
Gupta et al. [paper ] [code ]
[blog ]
2. Evolutionary Multitasking via Explicit autoencoding
TCYB
2018
Feng st al. [paper ] [code ]
[blog ]
3. A Group-based Approach to Improve Multifactorial Evolutionary Algorithm
IJCAI
2018
Tang st al. [paper ]
4. Self-regulated Evolutionary Multi-task Optimization
TEVC
2019
Zheng st al. [paper ] [code ]
[blog ]
5. MFEA-II Multifactorial Evolutionary Algorithm with Online Transfer Parameter Estimation MFEA-II
TEVC
2019
Bali st al. [paper ] [code ]
[blog ]
6. An Adaptive Archive-Based Evolutionary Framework for Many-Task Optimization
TETCI
2019
Chen st al. [paper ] [code ]
7. Evolutionary Manytasking Optimization Based on Symbiosis in Biocoenosis
AAAI
2019
Liaw st al. [paper ]
[blog ]
8. Regularized Evolutionary Multi-Task Optimization Learning to Inter-Task Transfer in Aligned Subspace
TEVC
2020
Tang st al. [paper ]
9. Solving Multi-task Optimization Problems with Adaptive Knowledge Transfer via Anomaly Detection
TEVC
2021
Wang st al. [paper ] [code ]
10. Evolutionary Multi-task Optimization with Adaptive Knowledge Transfer
TEVC
2021
Xu st al. [paper ]
11. Evolutionary Many-task Optimization Based on Multi-source Knowledge Transfer
TEVC
2021
Liang st al. [paper ]
12. Multi-Task Shape Optimization Using a 3D Point Cloud Autoencoder as Unified Representation
TEVC
2021
Rios st al. [paper ]
13. Towards Large-Scale Evolutionary Multi-Tasking: A GPU-Based Paradigm
TEVC
2021
Huang st al. [paper ]
14. Improving Evolutionary Multitasking Optimization by Leveraging Inter-Task Gene Similarity and Mirror Transformation
CIM
2021
Ma st al. [paper ]
15. A Bi-objective Knowledge Transfer Framework for Evolutionary Many-Task Optimization
TEVC
2022
Jiang st al. [paper ]
16. An Effective Knowledge Transfer Method Based on Semi-supervised Learning for Evolutionary Optimization
IS
2022
Gao st al. [paper ]
17. Orthogonal Transfer for Multitask Optimization
TEVC
2022
Wu st al. [paper ]
18. Multi-Task Particle Swarm Optimization With Dynamic Neighbor and Level-Based Inter-Task Learning
TETCI
2022
Tang st al. [paper ]
19. Evolutionary Competitive Multitasking Optimization
TEVC
2023
Li st al. [paper ]
20. Ensemble of Domain Adaptation-Based Knowledge Transfer for Evolutionary Multitasking
TEVC
2023
Lin st al. [paper ]
21. Ensemble Multifactorial Evolution with Biased Skill-Factor Inheritance for Many-task Optimization
TEVC
2022
Binh st al. [paper ]
22. Evolutionary Many-Task Optimization Based on Multisource Knowledge Transfer
TEVC
2022
Liang st al. [paper ]
23. Evolutionary Multitasking Optimization Enhanced by Geodesic Flow Kernel
TETCI
2023
Gao st al. [paper ]
24. Evolutionary Multitask Optimization With Lower Confidence Bound-Based Solution Selection Strategy
TEVC
2024
Wang st al. [paper ]
25. Multitask Evolution Strategy With Knowledge-Guided External Sampling
TEVC
2023
Li st al. [paper ]
26. Distributed Knowledge Transfer for Evolutionary Multitask Multimodal Optimization
TEVC
2023
Gao st al. [paper ]
27. Evolutionary Multitasking via Reinforcement Learning
TETCI
2023
Li st al. [paper ]
28. Federated Many-Task Bayesian Optimization
TEVC
2023
Li st al. [paper ]
29. Block-Level Knowledge Transfer for Evolutionary Multitask Optimization
TCYB
2023
Jiang st al. [paper ]
Multitasking Multi-objective Optimization
Paper Title
Venue
Year
Authors
Materials
Comment
1. Multiobjective Multifactorial Optimization in Evolutionary Multitasking
TCYB
2017
Gupta et al. [paper ] [code ]
2. Evolutionary Multitasking via Explicit autoencoding
TCYB
2018
Feng et al. [paper ] [code ]
3. Multiobjective Multitasking OptimizationBased on Incremental Learning
TEVC
2020
Lin et al. [paper ]
4. An Effective Knowledge Transfer Approach for Multiobjective Multitasking Optimization
TCYB
2020
Lin st al. [paper ] [code ]
5. Evolutionary Multitasking for Multiobjective Optimization With Subspace Alignmentand Adaptive Differential Evolution
TCYB
2020
Liang st al. [paper ] [code ]
6. Cognizant Multitasking in Multiobjective Multifactorial Evolution MO-MFEA-II
TCYB
2020
Bali et al. [paper ] [code ]
7. Multiobjective Multitasking Optimization Based on Decomposition with Dual Neighborhoods
arXiv
2021
Wang et al. [paper ]
8. Towards Generalized Resource Allocation on Evolutionary Multitasking for Multi-Objective Optimization
CIM
2021
Wei et al. [paper ]
9. Evolutionary Multitasking for Multi-objective Optimization Based on Generative Strategies
TEVC
2022
Liang et al. [paper ]
10. Dynamic Auxiliary Task-Based Evolutionary Multitasking for Constrained Multi-objective Optimization
TEVC
2022
Qiao et al. [paper ]
11. Multiobjective Multitask Optimization -Neighborhood as a Bridge for Knowledge Transfer
TEVC
2022
Wang et al. [paper ]
12. A Multi-objective Multitask Optimization Algorithm Using Transfer Rank
TEVC
2022
Chen et al. [paper ]
13. A Multiform Optimization Framework for Constrained Multiobjective Optimization
TCYB
2022
Jiao et al. [paper ]
14. Multiobjective Multitasking Optimization With Subspace Distribution Alignment and Decision Variable Transfer
TETCI
2022
Gao et al. [paper ]
15. Adaptive Auxiliary Task Selection for Multitasking-Assisted Constrained Multi-Objective Optimization [Feature]
CIM
2023
Ming et al. [paper ]
16. Multiobjective Evolutionary Multitasking With Two-Stage Adaptive Knowledge Transfer Based on Population Distribution
TSMC
2022
Liang et al. [paper ]
17. Learning Task Relationships in Evolutionary Multitasking for Multiobjective Continuous Optimization
TCYB
2022
Chen et al. [paper ]
18. A Self-Adaptive Evolutionary Multi-Task Based Constrained Multi-Objective Evolutionary Algorithm
TETCI
2023
Qiao et al. [paper ]
19. Evolutionary Multitasking for Large-Scale Multiobjective Optimization
TEVC
2022
Liu et al. [paper ]
20. An Evolutionary Multitasking Optimization Framework for Constrained Multiobjective Optimization Problems
TEVC
2022
Qiao et al. [paper ]
21. Constrained Multi-objective Optimization via Multitasking and Knowledge Transfer
TEVC
2022
Ming et al. [paper ]
22. A Multivariation Multifactorial Evolutionary Algorithm for Large-Scale Multiobjective Optimization
TEVC
2023
Feng et al. [paper ]
23. Multifactorial Evolutionary Algorithm Based on Improved Dynamical Decomposition for Many-Objective Optimization Problems
TEVC
2022
Yi et al. [paper ]
24. Multiobjective Multitask Optimization With Multiple Knowledge Types and Transfer Adaptation
TEVC
2024
Li et al. [paper ]
25. A Subspace-Knowledge Transfer Based Dynamic Constrained Multiobjective Evolutionary Algorithm
TETCI
2023
Chen et al. [paper ]
26. A Multi-Form Evolutionary Search Paradigm for Bi-level Multi-Objective Optimization
TEVC
2023
Feng et al. [paper ]
27. Dynamic Multiobjective Evolutionary Optimization via Knowledge Transfer and Maintenance
TSMC
2023
Lin et al. [paper ]
28. Evolutionary Multi-Objective Bayesian Optimization Based on Multisource Online Transfer Learning
TETCI
2023
Li et al. [paper ]
29. Multiple Tasks for Multiple Objectives: A New Multiobjective Optimization Method via Multitask Optimization
TEVC
2023
Li et al. [paper ]
30. Multiobjective Multitasking Optimization With Decomposition-Based Transfer Selection
TCYB
2023
Lin et al. [paper ]
Multitasking Combination Optimization
Paper Title
Venue
Year
Authors
Materials
Comment
1. Evolutionary Multitasking in Permutation-Based Combinatorial Optimization Problems Realization with TSP QAP LOP and JSP
TENCON
2016
Yuan et al. [paper ]
2. Evolutionary Multitasking in Combinatorial Search Spaces A Case Study in Capacitated Vehicle Routing Problem
SSCI
2016
Zhou et al. [paper ]
3. Solving Generalized Vehicle Routing Problem With Occasional Drivers via Evolutionary Multitasking
TCYB
2019
Feng st al. [paper ] [code ]
4. Explicit Evolutionary Multitasking for Combinatorial Optimization A Case Study on Capacitated Vehicle Routing Problem
TCYB
2020
Feng st al. [paper ] [code ]
5. A Unified Framework of Graph-based Evolutionary Multitasking Hyper-heuristic
TEVC
2021
Hao et al. [paper ]
6. Many-Objective Job-Shop Scheduling: A Multiple Populations for Multiple Objectives-Based Genetic Algorithm Approach
TCYB
2022
Liu et al. [paper ]
7. Transfer Learning Assisted Batch Optimization of Jobs Arriving Dynamically in Manufacturing Cloud
JOMS
2022
Zhou et al. [paper ]
8. Task Relatedness Based Multitask Genetic Programming for Dynamic Flexible Job Shop Scheduling
TEVC
2022
Zhang et al. [paper ]
9. Knowledge Transfer Genetic Programming with Auxiliary Population for Solving Uncertain Capacitated Arc Routing Problem
TEVC
2022
Ardeh et al. [paper ]
10. Multitask Multiobjective Genetic Programming for Automated Scheduling Heuristic Learning in Dynamic Flexible Job-Shop Scheduling
TCYB
2022
Zhang et al. [paper ]
11. Multitask Genetic Programming-Based Generative Hyperheuristics: A Case Study in Dynamic Scheduling
TCYB
2022
Zhang et al. [paper ]
12. Evolutionary Multitasking for Feature Selection in High-Dimensional Classification via Particle Swarm Optimization
TEVC
2022
Chen et al. [paper ]
13. Multitask Linear Genetic Programming with Shared Individuals and its Application to Dynamic Job Shop Scheduling
TEVC
2023
Huang et al. [paper ]
14. Using an Estimation of Distribution Algorithm to Achieve Multitasking Semantic Web Service Composition
TEVC
2023
Wang et al. [paper ]
15. Multitasking Evolutionary Algorithm Based on Adaptive Seed Transfer for Combinatorial Problem
ASOC
2023
Lv et al. [paper ]
Multitasking High-dimensional Optimization
Paper Title
Venue
Year
Authors
Materials
Comment
1. Large Scale optimization via Evolutionary Multitasking assisted Random Embedding
CEC
2020
Feng et al. [paper ]
2. A Multi-Variation Multifactorial Evolutionary Algorithm for Large-Scale Multi-Objective Optimization
TEVC
2021
Feng et al. [paper ]
3. Evolutionary Multitasking for Large-Scale Multiobjective Optimization
TEVC
2022
Liu et al. [paper ]
4. An Evolutionary Multitasking Algorithm with Multiple Filtering for High-Dimensional Feature Selection
TEVC
2023
Li et al. [paper ]
5. Evolutionary Optimization with Simplified Helper Task for High-dimensional Expensive Multiobjective Problems
ACM TELO
2024
Wu et al. [paper ]
6. Evolutionary Multitasking With Centralized Learning for Large-Scale Combinatorial Multi-Objective Optimization
TEVC
2023
Huang et al. [paper ]
7. Surrogate and Autoencoder-Assisted Multitask Particle Swarm Optimization for High-Dimensional Expensive Multimodal Problems
TEVC
2023
Ji et al. [paper ]
Multitasking Data-Driven Evolutionary Optimization
Paper Title
Venue
Year
Authors
Materials
Comment
1. Generalized Multi-tasking for Evolutionary Optimization of Expensive Problems
TEVC
2017
Ding et al. [paper ] [code ]
2. Novel Multitask Conditional Neural-Network Surrogate Models for Expensive Optimization
TCYB
2020
Luo et al. [paper ]
3. Evolutionary Multitasking for Expensive Minimax Optimization in Multiple Scenarios
CIM
2021
Wang et al. [paper ] [code ]
4. Multisurrogate-Assisted Multitasking Particle Swarm Optimization for Expensive Multimodal Problems
TCYB
2023
Ji et al. [paper ]
5. Investigating the Correlation Amongst the Objective and Constraints in Gaussian Process-Assisted Highly Constrained Expensive Optimization
TEVC
2022
Jiao et al. [paper ]
6. A Data-Driven Evolutionary Transfer Optimization for Expensive Problems in Dynamic Environments
TEVC
2023
Li et al. [paper ]
7. A Surrogate-Assisted Differential Evolution with Knowledge Transfer for Expensive Incremental Optimization Problems
TEVC
2023
Liu et al. [paper ]
Multitasking Genetic Programming and Swarm Intelligence
Paper Title
Venue
Year
Authors
Materials
Comment
1. Learning Ensemble of Decision Trees through Multifactorial Genetic Programming
CEC
2016
Wen et al. [paper ]
2. Multifactorial Genetic Programming for Symbolic Regression Problems
TSMC
2018
Zhong et al. [paper ]
3. Self-Adjusting Multi-Task Particle Swarm Optimization
TEVC
2021
Han et al. [paper ]
4. Self-adaptive Multi-task Particle Swarm Optimization
arxiv
2021
Zheng et al. [paper ]
5. Multi-Task Particle Swarm Optimization with Dynamic On-Demand Allocation
TEVC
2022
Han et al. [paper ]
6. Multi-Task Particle Swarm Optimization With Dynamic Neighbor and Level-Based Inter-Task Learning
TETCI
2022
Tang et al. [paper ]
7. A Multitask Bee Colony Band Selection Algorithm With Variable-Size Clustering for Hyperspectral Images
TEVC
2022
He et al. [paper ]
8. Learning and Sharing: A Multitask Genetic Programming Approach to Image Feature Learning
TEVC
2022
Bi et al. [paper ]
10. Multitask Particle Swarm Optimization with Heterogeneous Domain Adaptation
TEVC
2023
Han et al. [paper ]
11. A Meta-Knowledge Transfer-Based Differential Evolution for Multitask Optimization
TEVC
2022
Li et al. [paper ]
12. Privacy-Enhanced Multitasking Particle Swarm Optimization based on Homomorphic Encryption
TEVC
2023
Li et al. [paper ]
Multitasking Optimization in Complex Networks
Paper Title
Venue
Year
Authors
Materials
Comment
1. Evolutionary Multitasking Sparse Reconstruction Framework and Case Study
TEVC
2018
Li et al. [paper ]
2. MUMI Multitask Module Identification for Biological Networks
TEVC
2020
Chen et al. [paper ] [code ]
3. Evolutionary Multitasking Network Reconstruction from Time Series with Online Parameter Estimation
KBS
2021
Shen et al. [paper ]
4. Learning Large-Scale Fuzzy Cognitive Maps Using an Evolutionary Many-Task Algorithm
ASOC
2021
Wang et al. [paper ]
5. Evolutionary Multitasking Multilayer Network Reconstruction
TCYB
2021
Wang et al. [paper ] [code ]
6. Community detection in multiplex networks based on evolutionary multi-task optimization and evolutionary clustering ensemble
TEVC
2022
Lyu et al. [paper ]
7. A Multi-Transformation Evolutionary Framework for Influence Maximization in Social Networks
CIM
2023
Wang et al. [paper ]
8. Enhancing the Robustness of Networks Against Multiple Damage Models Using a Multifactorial Evolutionary Algorithm
TSMC
2023
Wang et al. [paper ]
Multitasking Optimization in Machine Learning
Paper Title
Venue
Year
Authors
Materials
Comment
1. Multi-task Bayesian Optimization
NIPS
2012
Swersky et al. [paper ]
2. Co-evolutionary Multi-Task Learning for Dynamic Time Series Prediction
ASOC
2018
Chandra et al. [paper ] [code ]
3. Adaptive Multi-factorial Evolutionary Optimization for Multi-task Reinforcement Learning
TEVC
2021
Martinez et al. [paper ] [code ]
4. Can Transfer Neuroevolution Tractably Solve Your Differential Equations
arXiv
2021
Huang et al. [paper ]
5. Simultaneously Evolving Deep Reinforcement Learning Models using Multifactorial Optimization
arXiv
2020
Martinez et al. [paper ] [code ]
6. Evolutionary Multitasking for Feature Selection in High-dimensional Classification via Particle Swarm Optimisation
TEVC
2021
Chen et al. [paper ]
7. Evolutionary Machine Learning with Minions: A Case Study in Feature Selection
TEVC
2021
Zhang et al. [paper ]
8. Learning and Sharing: A Multitask Genetic Programming Approach to Image Feature Learning
TEVC
2021
Bi et al. [paper ]
9. An Evolutionary Multitasking Method for Multiclass Classification [Research Frontier]
CIM
2022
Cheng et al. [paper ]
10. Evolutionary Multitasking AUC Optimization [Research Frontier]
CIM
2022
Wang et al. [paper ]
11. Adaptive Multifactorial Evolutionary Optimization for Multitask Reinforcement Learning
TEVC
2022
Martinez et al. [paper ]
12. ESSR: Evolving Sparse Sharing Representation for Multi-task Learning
TEVC
2023
Zhang et al. [paper ]
13. Towards Multi-Objective High-Dimensional Feature Selection via Evolutionary Multitasking
Arxiv
2024
Feng et al. [paper ]
14. Towards Evolutionary Multi-Task Convolutional Neural Architecture Search
TEVC
2023
Zhou et al. [paper ]
15. Jack and Masters of all Trades: One-Pass Learning Sets of Model Sets From Large Pre-Trained Models
CIM
2023
Choong et al. [paper ]
16. A Fast Evolutionary Knowledge Transfer Search for Multiscale Deep Neural Architecture
TNNLS
2023
Zhang et al. [paper ]
17. Training Physics-Informed Neural Networks via Multi-Task Optimization for Traffic Density Prediction
Arxiv
2023
Wang et al. [paper ]
Paper Title
Venue
Year
Authors
Materials
Comment
1. Insights on Transfer Optimization Because Experience is the Best Teacher
TETCI
2018
Gupta et al. [paper ]
2. Curbing Negative Influences Online for Seamless Transfer Evolutionary Optimization
TCYB
2019
Da et al. [paper ] [code ]
3. Warm Starting CMA-ES for Hyperparameter Optimization
AAAI
2020
Nomura et al. [paper ]
4. Generalizing Transfer Bayesian Optimization to Source-Target Heterogeneity
TASE
2020
Min et al. [paper ]
5. Scalable Transfer Evolutionary Optimization Coping with Big Task Instances
arXiv
2020
Shakeri et al. [paper ] [code ]
6. Transfer Stacking from Low-to High-Fidelity A Surrogate-Assisted Bi-Fidelity Evolutionary Algorithm
ASOC
2020
Wang et al. [paper ] [code ]
7. Transfer Learning Based Co-surrogate Assisted Evolutionary Bi-objective Optimization for Objectives with Non-uniform Evaluation Times
arxiv
2021
Wang et al. [paper ]
8. Evolutionary Sequential Transfer Optimization for Objective-Heterogeneous Problems
TEVC
2022
Xue st al. [paper ]
9. Transfer Learning Based Co-Surrogate Assisted Evolutionary Bi-Objective Optimization for Objectives with Non-Uniform Evaluation Times
EC
2022
Wang et al. [paper ]
10. ExTrEMO: Transfer Evolutionary Multiobjective Optimization With Proof of Faster Convergence
TEVC
2024
Liu et al. [paper ]
11. Inverse Transfer Multiobjective Optimization
Arxiv
2023
Liu et al. [paper ]
12. Solution Transfer in Evolutionary Optimization: An Empirical Study on Sequential Transfer
TEVC
2023
Xue et al. [paper ]
13. Transfer-Based Particle Swarm Optimization for Large-Scale Dynamic Optimization With Changing Variable Interactions
TEVC
2023
Liu et al. [paper ]
14. A Data-Driven Evolutionary Transfer Optimization for Expensive Problems in Dynamic Environments
TEVC
2023
Li et al. [paper ]
15. First Complexity Results for Evolutionary Knowledge Transfer
FOGA
2023
Eric O Scott et al. [paper ]
Paper Title
Venue
Year
Authors
Materials
Comment
1. Improve Theoretical Upper Bound of Jumpk Function by Evolutionary Multitasking
HPCCT
2019
Lian et al. [paper ]
2. Analysis on the Efficiency of Multifactorial Evolutionary Algorithms
PPSN
2020
Huang et al. [paper ]
3. From Multi-Task Gradient Descent to Gradient-Free Evolutionary Multitasking A Proof of Faster Convergence
TCYB
2021
Bai et al. [paper ]
Paper Title
Venue
Year
Authors
Materials
Comment
1. Evolutionary Multitasking In Bi-Level Optimization
Complex & Intelligent Systems
2015
Gupta et al. [paper ]
2. An Evolutionary Multitasking Algorithm for Cloud Computing Service Composition
World Congress on Services
2018
Bao st al. [paper ]
3. Multi-Tasking Genetic Algorithm (MTGA)
TFS
2019
Wu et al. [paper ]
[blog ]
4. A Multitasking Electric Power Dispatch Approach With Multi-Objective Multifactorial Optimization Algorithm
Access
2020
Liu et al. [paper ]
5. Solving Dynamic Multiobjective Problem via Autoencoding Evolutionary Search
TCYB
2020
Liang et al. [paper ] [code ]
6. A Multi-Task Bee Colony Band Selection Algorithm with Variable-size Clustering for Hyperspectral Images
TEVC
2022
He et al. [paper ]
7. Predicting Demands of COVID-19 Prevention and Control Materials via Co-Evolutionary Transfer Learning
TCYB
2022
Song et al. [paper ]
8. Multi-View Point Cloud Registration Based on Evolutionary Multitasking With Bi-Channel Knowledge Sharing Mechanism
TETCI
2022
Wu et al. [paper ]
9. Evolutionary Multitasking for Costly Task Offloading in Mobile Edge Computing Networks
TEVC
2022
Yang et al. [paper ]
10. Multitask Shape Optimization Using a 3-D Point Cloud Autoencoder as Unified Representation
TEVC
2022
Rios et al. [paper ]
11. Evolutionary Multiform Optimization with Two-stage Bidirectional Knowledge Transfer Strategy for Point Cloud Registration
TEVC
2022
Wu et al. [paper ]
12. Evolutionary Multitasking Optimization Enhanced by Geodesic Flow Kernel
TETCI
2023
Gao et al. [paper ]
13. Evolutionary Multitasking With Solution Space Cutting for Point Cloud Registration
TETCI
2023
Wu et al. [paper ]
Paper Title
Venue
Year
Authors
Materials
Comment
1. Evolutionary Multitasking for Single-objective Continuous Optimization Benchmark Problems Performance Metric and Baseline Results
arXiv
2017
Da et al. [paper ] [code ]
2. Evolutionary Multitasking for Multiobjective Continuous Optimization Benchmark Problems Performance Metrics and Baseline Results
arXiv
2017
Yuan et al. [paper ] [code ]
3. Evolutionary Multitasking Optimization for Complex Problems
CEC, GECCO
2017~2021
Feng et al. [code ]
4. Evolutionary Many-tasking Optimization
CEC, GECCO
2017~2021
Feng et al. [code ]
5. Evolutionary Transfer Optimization
CEC
2021
Tan et al. [paper ] [code ]
6. Evolutionary Constrained Multiobjective Optimization: Scalable High-Dimensional Constraint Benchmarks and Algorithm
TEVC
2023
Qiao et al. [paper ] [code ]
Name
Authors/Organizations
Materials
Comment
1. Deap
Fortin et al. [paper ] [code ]
DEAP is a novel evolutionary computation framework for rapid prototyping and testing of ideas. It seeks to make algorithms explicit and data structures transparent. It works in perfect harmony with parallelisation mechanisms such as multiprocessing and SCOOP .
2. Geatpy2
South China Agricultural University et al. [homepage ] [code ]
Capability of solving single-objective, multi-objectives, many-objectives and combinatorial optimization problems fast. A huge number of operators with high performance of evolutionary algorithms (selection, recombination, mutation, migration...). Support numerous encodings for the chromosome of the population. Many evolutionary algorithm templates, including GA, DE, ES for single/multi-objective(s) evolution. Multiple population evolution. Support polysomy evolution. Parallelization and distribution of evaluations. Testbeds containing most common benchmarks functions. Support tracking analysis of the evolution iteration. Many evaluation metrics of algorithms.
3. Inspyred
Garrett et al. [homepage ] [code ]
Inspyred is a free, open source framework for creating biologically-inspired computational intelligence algorithms in Python, including evolutionary computation, swarm intelligence, and immunocomputing. Additionally, inspyred provides easy-to-use canonical versions of many bio-inspired algorithms for users who do not need much customization.
4. PlatEMO
Tian et al. [paper ] [code ]
Developed by BIMK (Institute of Bioinspired Intelligence and Mining Knowledge) of Anhui University and NICE (Nature Inspired Computing and Engineering Group) of University of Surrey. 150+ open source evolutionary algorithms, 300+ open source benchmark problems, Powerful GUI for performing experiments in parallel, Generating results in the format of Excel or LaTeX table by one-click operation, State-of-the-art algorithms will be included continuously.
5. EvoGrad
Uber AI Labs [code ]
EvoGrad is a lightweight tool for differentiating through expectation, built on top of PyTorch. EvoGrad enables fast prototyping of NES-like algorithms. We believe there are many interesting algorithms yet to be discovered in this vein, and we hope this library will help to catalyze progress in the machine learning community.
6. MToP
Li et al. [paper ] [code ]
MToP provides a user-friendly GUI, enriched algorithms and problems, and convenient code patterns. The current version of MToP includes more than 30 MTEAs, more than 30 single-task EAs (that can handle MTO problems), more than 150 MTO benchmark problems, and several real-world applications of EMT.
Disclaimer
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Emails: xiaofengxd@126.com
Authors of scientific papers including results generated using MTEA-AD or EM2MNR are encouraged to cite the following paper:
@ARTICLE{9489377, author={Wu, Kai and Wang, Chao and Liu, Jing}, journal={IEEE Transactions on Cybernetics}, title={Evolutionary Multitasking Multilayer Network Reconstruction}, year={2022}, volume={52}, number={12}, pages={12854-12868}, doi={10.1109/TCYB.2021.3090769}}
@ARTICLE{9385398, author={Wang, Chao and Liu, Jing and Wu, Kai and Wu, Zhaoyang}, journal={IEEE Transactions on Evolutionary Computation}, title={Solving Multitask Optimization Problems With Adaptive Knowledge Transfer via Anomaly Detection}, year={2022}, volume={26}, number={2}, pages={304-318}, doi={10.1109/TEVC.2021.3068157}}
@article{WANG2021107441,
title = {Learning large-scale fuzzy cognitive maps using an evolutionary many-task algorithm},
journal = {Applied Soft Computing},
volume = {108},
pages = {107441},
year = {2021},
issn = {1568-4946},
doi = {https://doi.org/10.1016/j.asoc.2021.107441} ,
url = {https://www.sciencedirect.com/science/article/pii/S1568494621003641} ,
author = {Chao Wang and Jing Liu and Kai Wu and Chaolong Ying}}