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2014

Refereed Journal Papers

  1. Bo Yuan, Bin Li, Thomas Weise, and Xin Yao. A New Memetic Algorithm With Fitness Approximation for the Defect-Tolerant Logic Mapping in Crossbar-Based Nanoarchitectures. IEEE Transactions on Evolutionary Computation (IEEE-EC), 18(6):846-459, December 2014.
  2. X. Lu, K. Tang*, B. Sendhoff and Xin Yao. A New Self-adaptation Scheme for Differential Evolution, Neurocomputing, 146: 2-16, December 2014.
  3. Ke Tang*, F. Peng, G. Chen and Xin Yao. Population-based Algorithm Portfolios with automated constituent algorithms selection, Information Sciences, 279: 94-104, September 2014.
  4. Thomas Weise, Raymond Chiong, Ke Tang, Jörg Lässig, Shigeyoshi Tsutsui, Wenxiang Chen, Zbigniew Michalewicz, and Xin Yao. Benchmarking Optimization Algorithms: An Open Source Framework for the Traveling Salesman Problem. IEEE Computational Intelligence Magazine (CIM), 9(3):40-52, August 2014. Featured article and selected paper at the website of the IEEE Computational Intelligence Society (http://cis.ieee.org/).
  5. Thomas Weise, Mingxu Wan, Ke Tang, Pu Wang, Alexandre Devert, and Xin Yao. Frequency Fitness Assignment, IEEE Transactions on Evolutionary Computation, 18(2):226-243, April 2014.
  6. Bo Yuan and Bin Li. A Fast Extraction Algorithm for Defect-free Subcrossbar in Nanoelectronic Crossbar, ACM Journal on Emerging Technologies in Computing Systems, vol. 10, no. 3, article 25, April 2014.
  7. X. Lu, Ke Tang, B. Sendhoff and Xin Yao. A Review of Concurrent Optimization Methods, International Journal of Bio-inspired Computation, 6(1): 22-31, March 2014.
  8. Pu Wang, Ke Tang, Thomas Weise, Edward P. K. Tsang, and Xin Yao, Multiobjective Genetic Programming for Maximizing ROC Performance, Neurocomputing, 125:102-118, February 2014.
  9. Shan He, Huanhuan Chen, Zexuan Zhu, et al. Robust Twin Boosting for Feature Selection from High-dimensional Omics Data with Label Noise, Information Science, 291:1–18, 2015, DOI: 10.1016/j.ins.2014.08.048.
  10. Huanhuan Chen, Peter Tiňo, and Xin Yao. Cognitive Fault Diagnosis in Tennessee Eastman Process using Learning in the Model Space. Computers & Chemical Engineering, 2014. 10.1016/j.compchemeng.2014.03.015 [download]
  11. Huanhuan Chen, Peter Tiňo, Ali Rodan, Xin Yao. Learning in the Model Space for Cognitive Fault Diagnosis. IEEE Transactions on Neural Networks and Learning Systems, 25(1): 124-136 (2014). [download]
  12. Huanhuan Chen, Peter Tiňo, Xin Yao. Efficient Probabilistic Classification Vector Machine With Incremental Basis Function Selection. IEEE Transactions on Neural Networks and Learning Systems, 25(2): 356-369 (2014). [download]
  13. Joseba Quevedo, Huanhuan Chen, Miquel A. Cuguero, Peter Tino, Vicenc Puig, D. Garcia, R. Sarrate and Xin Yao. Combining Learning in Model Space Fault Diagnosis with Data Validation/Reconstruction: Application to the Barcelona Water Network. Engineering Applications of Artificial Intelligence, 30: 18-29, (2014). [download]
  14. Qi Guo, Tianshi Chen, Yunji Chen, Rui Wang, Huanhuan Chen, Weiwu Hu, Guoliang Chen. Pre-Silicon Bug Forecast. IEEE Transactions on CAD of Integrated Circuits and Systems, 33(3): 451-463 (2014). [download]

Refereed Conference Papers

  1. Yan Jiang, Thomas Weise, Jörg Lässig, Raymond Chiong, and Rukshan Athauda. Comparing a Hybrid Branch and Bound Algorithm with Evolutionary Computation Methods, Local Search and their Hybrids on the TSP. In: Proceedings of the IEEE Symposium on Computational Intelligence in Production and Logistics Systems (CIPLS’14), Proceedings of the IEEE Symposium Series on Computational Intelligence (SSCI’14), Orlando, FL, USA: Caribe Royale All-Suite Hotel and Convention Center, December 9–12, 2014. Los Alamitos, CA, USA: IEEE Computer Society Press.
  2. Abhishek Awasthi, Jörg Lässig, Oliver Kramer, and Thomas Weise. Common Due-Window Problem: Polynomial Algorithms for a Given Processing Sequence. In: Proceedings of the IEEE Symposium on Computational Intelligence in Production and Logistics Systems (CIPLS’14), Proceedings of the IEEE Symposium Series on Computational Intelligence (SSCI’14), Orlando, FL, USA: Caribe Royale All-Suite Hotel and Convention Center, December 9–12, 2014. Los Alamitos, CA, USA: IEEE Computer Society Press.
  3. Chao Gao, Thomas Weise, and Jinlong Li. Improve the 3-flip Neighborhood Local Search by Random Flat Move for the Set Covering Problem. In: Ying Tan, Yuhui Shi, and Carlos Artemio Coello Coello, editors, Advances in Swarm Intelligence: Proceedings of the Fifth International Conference on Swarm Intelligence, Part 1 (ICSI’14), volume 8794 of Lecture Notes in Computer Science (LNCS), pages 27-35, Hefei, Anhui, China, October 17–20, 2014. Berlin, Germany: Springer-Verlag GmbH.
  4. Tiantian Huang and Bin Li, A Genetic Algorithm using Priority-based Encoding for RSA in Elastic Optical Network, ICICTA 2014, Changsha, China, October 2014.
  5. T. Chen, Q. Guo, K. Tang, O. Temam, Z. Xu, Z.-H. Zhou, and Y. Chen, ArchRanker: A ranking approach to design space exploration, In: Proceedings of the 41st International Symposium on Computer Architecture (ISCA'14), Minneapolis, MN, 2014, pp.85-96.
  6. Kai Zhang, Thomas Weise, and Jinlong Li. Fitness Level based Adaptive Operator Selection for Cutting Stock Problems with Contiguity. In: Proceedings of the IEEE Congress on Evolutionary Computation (CEC’14), Proceedings of the 2014 World Congress on Computational Intelligence (WCCI’14), pages 2539-2546, Beijing, China: Beijing International Convention Center (BICC), July 6–11, 2014. Los Alamitos, CA, USA: IEEE Computer Society Press.
  7. Thomas Weise, Mingxu Wan, Ke Tang, and Xin Yao. Evolving Exact Integer Algorithms with Genetic Programming. In: Proceedings of the IEEE Congress on Evolutionary Computation (CEC’14), Proceedings of the 2014 World Congress on Computational Intelligence (WCCI’14), pages 1816-1823, Beijing, China: Beijing International Convention Center (BICC), July 6–11, 2014. Los Alamitos, CA, USA: IEEE Computer Society Press.
  8. Bingdong Li, Jinlong Li, Ke Tang, and Xin Yao. An improved Two Archive Algorithm for Many-Objective optimization, IEEE Congress on Evolutionary Computation (CEC), 2014 pages 2869-2876, 6-11 July 2014
  9. Chao Gao, Thomas Weise, and Jinlong Li. A Weighting-Based Local Search Heuristic Algorithm for the Set Covering Problem. In: Proceedings of the IEEE Congress on Evolutionary Computation (CEC’14), Proceedings of the 2014 World Congress on Computational Intelligence (WCCI’14), pages 826-831, Beijing, China: Beijing International Convention Center (BICC), July 6–11, 2014. Los Alamitos, CA, USA: IEEE Computer Society Press.
  10. Can Liu and Bin Li. Memetic Algorithm with Adaptive Local Search Depth for Large Scale Global Optimization, 2014 IEEE World Congress on Computational Intelligence (WCCI2014), Beijing, China, pages 82-88, 2014.
  11. Fugui Zhong, Bo Yuan and Bin Li. Hybridization of NSGA-II with greedy re-assignment for variation tolerant logic mapping on nano-scale crossbar architectures. In: GECCO 2014, Vancouver, Canada, July 2014.
  12. H. Fu, P. R. Lewis, B. Sendhoff, Ke Tang, and Xin Yao. What Are Dynamic Optimization Problems? In: Proceedings of the 2014 IEEE Congress on Evolutionary Computation (CEC2014), Beijing, China, July 6-11, 2014, pp. 1550-1557.
  13. J. Zhong, K. Tang and A. K. Qin. Finding Convex Hull Vertices in Metric Space, In: Proceedings of the 2014 International Joint Conference on Neural Networks, Beijing, China, July 6-11, 2014, pp. 1587-1592.
  14. P. Yang, Ke Tang and J. A. Lozano. Estimation of Distribution Algorithms based Unmanned Aerial Vehicle Path Planner Using a New Coordinate System, In: Proceedings of the 2014 IEEE Congress on Evolutionary Computation (CEC2014), Beijing, China, July 6-11, 2014, pp. 1469-1476
  15. Can Liu and Bin Li. Individual-based Cooperative Coevolution Local Search for Large Scale Optimization, In: 2014 Asia Pacific Symposium on Intelligent and Evolutionary Systems, Vol. 1, Singapore, pages 535-547, 2014.
  16. J. Li and M. Yan. Pareto Partial Dominance on Two Selected Objectives MOEA on Many-Objective 0/1 Knapsack Problems. In: Advances in Swarm Intelligence, pages 365-373. Springer International Publishing.
  17. Fengzhen Tang, Peter Tiño, Huanhuan Chen. Learning the deterministically constructed Echo State Networks. In: Proceedings of the 2014 International Joint Conference on Neural Networks (IJCNN'14), 2014: 77-83
  18. Fengzhen Tang, Peter Tiño, Pedro Antonio Gutiérrez, and Huanhuan Chen. Support Vector Ordinal Regression using Privileged Information. In: ESANN 2014