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ORCIDSwarm and Evolutionary Computation, Volume 52
Volume 52, February 2020
- Lourdes Uribe
, Adriana Lara, Oliver Schütze:
On the efficient computation and use of multi-objective descent directions within constrained MOEAs. - Haopeng Zhang:
A discrete-time switched linear model of the particle swarm optimization algorithm. - Milosz Kadzinski, Michal K. Tomczyk, Roman Slowinski:
Preference-based cone contraction algorithms for interactive evolutionary multiple objective optimization. - Ismail M. Ali, Daryl Essam, Kathryn Kasmarik:
A novel design of differential evolution for solving discrete traveling salesman problems. - Rumana Nazmul, Madhu Chetty, Ahsan Raja Chowdhury:
Multimodal Memetic Framework for low-resolution protein structure prediction. - Ashraf Darwish, Dalia Ezzat, Aboul Ella Hassanien:
An optimized model based on convolutional neural networks and orthogonal learning particle swarm optimization algorithm for plant diseases diagnosis. - Ping Tan, Xin Wang, Yong Wang:
Dimensionality reduction in evolutionary algorithms-based feature selection for motor imagery brain-computer interface. - Oliver Cuate, Lourdes Uribe, Adriana Lara, Oliver Schütze:
A benchmark for equality constrained multi-objective optimization. - Junqing Li, Xin-rui Tao, Baoxian Jia, Yu-Yan Han, Chuang Liu, Peng Duan, Zhi-xin Zheng, Hong-yan Sang:
Efficient multi-objective algorithm for the lot-streaming hybrid flowshop with variable sub-lots. - Rafal Biedrzycki:
Handling bound constraints in CMA-ES: An experimental study. - Nádia Junqueira Martarelli, Marcelo Seido Nagano:
Unsupervised feature selection based on bio-inspired approaches. - Pratyusha Rakshit:
Improved differential evolution for noisy optimization. - Qi Li, Zehong Cao, Weiping Ding, Qing Li:
A multi-objective adaptive evolutionary algorithm to extract communities in networks.
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