Evolutionary Computation for Dynamic Optimisation in Network Environments

Research output

Research output per year 2014 2015 2016 2017 2018 2020

• 19 Article
• 1 Conference contribution

Research output per year

Research output per year

Search results

• 2020

  A task-oriented heuristic for repairing infeasible solutions to overlapping coalition structure generation

  Zhang, G., Su, Z., Li, M., Qi, M., Jiang, J. & Yao, X., Mar 2020, In: IEEE Transactions on Systems, Man and Cybernetics: Systems. 50, 3, p. 785-801 17 p.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  File

  • Repair 100%
  • Heuristic algorithms 60%
  • Multi agent systems 57%
  • Computational complexity 49%
  1 Citation (Scopus)

  171 Downloads (Pure)
• 2018

  A Systematic Study of Online Class Imbalance Learning With Concept Drift

  Wang, S., Minku, L. L. & Yao, X., Oct 2018, In: IEEE Transactions on Neural Networks and Learning Systems. 29, 10, p. 4802-4821 20 p.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  File

  • Data streams 100%
  64 Citations (Scopus)

  312 Downloads (Pure)

• Dynamic Multi-Objectives Optimization with a Changing Number of Objectives

  Chen, R., Li, K. & Yao, X., Feb 2018, In: IEEE Transactions on Evolutionary Computation. 22, 1, p. 157-171 33 p.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  File

  • Dynamic Optimization 100%
  • Multi-objective Optimization 86%
  • Multiobjective optimization 65%
  • Objective function 29%
  • Dynamic Optimization Problems 25%
  52 Citations (Scopus)

  329 Downloads (Pure)

• Evolutionary Multiobjective Optimization Based Multimodal Optimization: Fitness Landscape Approximation and Peak Detection

  Cheng, R., Li, M., Li, K. & Yao, X., Oct 2018, In: IEEE Transactions on Evolutionary Computation. 22, 5, p. 692 - 706 15 p.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  File

  • Multimodal Optimization 100%
  • Evolutionary multiobjective Optimization 93%
  • Fitness Landscape 82%
  • Multiobjective optimization 54%
  • Multiobjective Optimization Problems 35%
  31 Citations (Scopus)

  190 Downloads (Pure)

• FEMOSAA: Feature-guided and knEe-driven Multi-Objective optimization for Self-Adaptive softwAre

  Chen, T., Li, K., Bahsoon, R. & Yao, X., 19 Jul 2018, In: ACM Transactions on Software Engineering and Methodology. 27, 2, 50 p., 5.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  File

  • Multiobjective optimization 100%
  • Evolutionary algorithms 41%
  • Chromosomes 17%
  • Mathematical operators 13%
  • Energy utilization 10%
  208 Downloads (Pure)

• Multi-line distance minimization: a visualized many-objective test problem suite

  Li, M., Grosan, C., Yang, S., Liu, X. & Yao, X., Feb 2018, In: IEEE Transactions on Evolutionary Computation. 22, 1, p. 61-78 18 p.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  File

  • Test Problems 100%
  • Minimization Problem 95%
  • Line 68%
  • Performance Indicators 42%
  • Evolutionary Optimization 39%
  26 Citations (Scopus)

  239 Downloads (Pure)

• R-Metric: Evaluating the Performance of Preference-Based Evolutionary Multi-Objective Optimization Using Reference Points

  Li, K., Deb, K. & Yao, X., Dec 2018, In: IEEE Transactions on Evolutionary Computation. 22, 6, p. 821 - 835 23 p.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  File

  • Evolutionary multiobjective Optimization 100%
  • Reference Point 82%
  • Multiobjective optimization 58%
  • Metric 40%
  • Performance 36%
  33 Citations (Scopus)

  200 Downloads (Pure)
• 2017

  Average Drift Analysis and Population Scalability

  He, J. & Yao, X., Jun 2017, In: IEEE Transactions on Evolutionary Computation. 21, 3, p. 426-439 26 p.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  File

  • Scalability 100%
  • Evolutionary algorithms 70%
  • Hitting Time 63%
  • Population Density 62%
  • Evolutionary Algorithms 46%
  8 Citations (Scopus)

  126 Downloads (Pure)

• DG2: A Faster and More Accurate Differential Grouping for Large-Scale Black-Box Optimization

  Omidvar, M. N., Yang, M., Mei, Y., Li, X. & Yao, X., 25 Apr 2017, (E-pub ahead of print) In: IEEE Transactions on Evolutionary Computation.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  File

  • Black-box Optimization 100%
  • Large-scale Optimization 82%
  • Grouping 71%
  • Interaction 44%
  • Objective function 34%
  109 Citations (Scopus)

  234 Downloads (Pure)

• Efficient Resource Allocation in Cooperative Co-evolution for Large-scale Global Optimization

  Yang, M., Omidvar, M. N., Li, C., Li, X., Cai, Z., Kazimipour, B. & Yao, X., Aug 2017, In: IEEE Transactions on Evolutionary Computation. 21, 4, p. 493-505 13 p.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  File

  • Cooperative Coevolution 100%
  • Large-scale Optimization 70%
  • Resource Allocation 70%
  • Global optimization 55%
  • Global Optimization 55%
  53 Citations (Scopus)

  293 Downloads (Pure)

• Turning high-dimensional optimization into computationally expensive optimization

  Yang, P., Tang, K. & Yao, X., 22 Feb 2017, (E-pub ahead of print) In: IEEE Transactions on Evolutionary Computation.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  File

  • High-dimensional 100%
  • Optimization 92%
  • Global optimization 63%
  • Divide and conquer 40%
  • Empirical Study 34%
  32 Citations (Scopus)

  231 Downloads (Pure)
• 2016

  A competitive divide-and-conquer algorithm for unconstrained large-scale black-box optimization

  Mei, Y., Omidvar, M. N., Li, X. & Yao, X., Jun 2016, In: ACM Transactions on Mathematical Software. 42, 2, 25 p., 13.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  File

  • Black-box Optimization 100%
  • Divide-and-conquer Algorithm 91%
  • Large-scale Optimization 82%
  • Grouping 71%
  • Covariance Matrix Adaptation 68%
  69 Citations (Scopus)

  542 Downloads (Pure)

• A Scalable Approach to Capacitated Arc Routing Problems Based on Hierarchical Decomposition

  Tang, K., Wang, J., Li, X. & Yao, X., 4 Aug 2016, (E-pub ahead of print) In: IEEE Transactions on Cybernetics. PP, 99, p. 1-13

  Research output: Contribution to journal › Article › peer-review

  Open Access

  File

  • Decomposition 100%
  • Scalability 37%
  23 Citations (Scopus)

  269 Downloads (Pure)

• Defect- and Variation-tolerant Logic Mapping in Nano-crossbar Using Bipartite Matching and Memetic Algorithm

  Yuan, B., Li, B., Chen, H. & Yao, X., 23 Aug 2016, In: IEEE Transactions on Very Large Scale Integration (VLSI) Systems. 24, 9, p. 2813-2826 14 p.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  File

  • Defects 100%
  • Defect density 34%
  • Adders 26%
  • Simulated annealing 24%
  • Heuristic algorithms 24%
  8 Citations (Scopus)

  182 Downloads (Pure)

• Dynamic Software Project Scheduling through a Proactive-rescheduling Method

  Shen, X., Minku, L., Bahsoon, R. & Yao, X., 1 Jul 2016, In: IEEE Transactions on Software Engineering. 42, 7, p. 658 - 686

  Research output: Contribution to journal › Article › peer-review

  Open Access

  File

  • Scheduling 100%
  • Evolutionary algorithms 14%
  • Deterioration 14%
  • Software engineering 13%
  • Mathematical models 11%
  29 Citations (Scopus)

  405 Downloads (Pure)

• Stochastic Ranking Algorithm for Many-Objective Optimization Based on Multiple Indicators

  Li, B., Tang, K., Li, J. & Yao, X., 1 Dec 2016, In: IEEE Transactions on Evolutionary Computation. 20, 6, p. 924 - 938 15 p.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  File

  • Ranking 100%
  • Pareto Front 87%
  • Optimization 74%
  • Empirical Study 44%
  • Multi-objective Evolutionary Algorithm 30%
  100 Citations (Scopus)

  270 Downloads (Pure)
• 2015

  A Survey on Problem Models and Solution Approaches to Rescheduling in Railway Networks

  Fang, W., Yang, S. & Yao, X., 1 Dec 2015, In: IEEE Transactions on Intelligent Transportation Systems. 16, 6, p. 2997-3016

  Research output: Contribution to journal › Article › peer-review

  Open Access
  96 Citations (Scopus)

• Mathematical modeling and multi-objective evolutionary algorithms applied to dynamic flexible job shop scheduling problems

  Shen, X. & Yao, X., 20 Mar 2015, In: Information Sciences. 298, p. 198-224

  Research output: Contribution to journal › Article › peer-review

  Open Access

  File

  • Job shop scheduling 100%
  • Evolutionary algorithms 72%
  • Decision making 16%
  • Scheduling 15%
  • Mathematical models 7%
  121 Citations (Scopus)

  989 Downloads (Pure)

• Robust optimization over time: problem difficulties and benchmark problems

  Fu, H., Sendhoff, B., Tang, K. & Yao, X., 1 Oct 2015, In: IEEE Transactions on Evolutionary Computation. 19, 5, p. 731-745

  Research output: Contribution to journal › Article › peer-review

  Open Access

  File

  • Robust Optimization 100%
  • Benchmark 73%
  • Dynamic Optimization Problems 36%
  • Fitness 18%
  • Experimental Results 16%
  29 Citations (Scopus)

  240 Downloads (Pure)
• 2014

  What are dynamic optimization problems?

  Fu, H., Lewis, P. R., Sendhoff, B., Tang, K. & Yao, X., 16 Sept 2014, Proceedings of the 2014 IEEE Congress on Evolutionary Computation, CEC 2014. Institute of Electrical and Electronics Engineers (IEEE), p. 1550-1557 8 p. 6900316

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Dynamic Optimization Problems 100%
  • Evolutionary Optimization 58%
  • Reinforcement Learning 57%
  • Dynamic Optimization 54%
  • Evolutionary Dynamics 52%
  14 Citations (Scopus)