MOEA/D
MOEA/D framework. An experimental analysis of evolutionary heuristics for the biobjective traveling purchaser problem (2TPP)
Keywords for this software
References in zbMATH (referenced in 216 articles )
Showing results 1 to 20 of 216.
Sorted by year (- Wen, Tao; Ge, Quanbo; Lyu, Xinan; Chen, Lei; Constantinou, Costas; Roberts, Clive; Cai, Baigen: A cost-effective wireless network migration planning method supporting high-security enabled railway data communication systems (2021)
- Abouhawwash, Mohamed; Jameel, Mohammed; Deb, Kalyanmoy: A smooth proximity measure for optimality in multi-objective optimization using Benson’s method (2020)
- Belabid, Jabrane; Aqil, Said; Allali, Karam: Solving permutation flow shop scheduling problem with sequence-independent setup time (2020)
- Binois, Mickael; Picheny, Victor; Taillandier, Patrick; Habbal, Abderrahmane: The Kalai-Smorodinsky solution for many-objective Bayesian optimization (2020)
- Chen, Hanshu; Meng, Zeng; Zhou, Huanlin: A hybrid framework of efficient multi-objective optimization of stiffened shells with imperfection (2020)
- Chen, Huangke; Cheng, Ran; Wen, Jinming; Li, Haifeng; Weng, Jian: Solving large-scale many-objective optimization problems by covariance matrix adaptation evolution strategy with scalable small subpopulations (2020)
- Chen, Wentao; Han, Fei: An improved multi-objective particle swarm optimization with adaptive penalty value for feature selection (2020)
- Dong, Nan-jiang; Wang, Rui: MEAPCA: a multi-population evolutionary algorithm based on PCA for multi-objective optimization (2020)
- Drake, John H.; Starkey, Andrew; Owusu, Gilbert; Burke, Edmund K.: Multiobjective evolutionary algorithms for strategic deployment of resources in operational units (2020)
- Felipe Campelo, Lucas Batista, Claus Aranha: The MOEADr Package: A Component-Based Framework for Multiobjective Evolutionary Algorithms Based on Decomposition (2020) not zbMATH
- Filatovas, E.; Kurasova, O.; Redondo, J. L.; Fernández, J.: A reference point-based evolutionary algorithm for approximating regions of interest in multiobjective problems (2020)
- Hamada, Naoki; Hayano, Kenta; Ichiki, Shunsuke; Kabata, Yutaro; Teramoto, Hiroshi: Topology of Pareto sets of strongly convex problems (2020)
- Jiang, Shouyong; Li, Hongru; Guo, Jinglei; Zhong, Mingjun; Yang, Shengxiang; Kaiser, Marcus; Krasnogor, Natalio: AREA: an adaptive reference-set based evolutionary algorithm for multiobjective optimisation (2020)
- Liang, Liang: A fusion multiobjective empire split algorithm (2020)
- Liu, Ruochen; Zhou, Runan; Ren, Rui; Liu, Jiangdi; Jiao, Licheng: Multi-layer interaction preference based multi-objective evolutionary algorithm through decomposition (2020)
- Liu, Yuan; Zhu, Ningbo; Li, Kenli; Li, Miqing; Zheng, Jinhua; Li, Keqin: An angle dominance criterion for evolutionary many-objective optimization (2020)
- Liu, Zhi-Zhong; Wang, Yong; Huang, Pei-Qiu: AnD: a many-objective evolutionary algorithm with angle-based selection and shift-based density estimation (2020)
- Ma, Lianbo; Wang, Rui; Chen, Shengminjie; Cheng, Shi; Wang, Xingwei; Lin, Zhiwei; Shi, Yuhui; Huang, Min: A novel many-objective evolutionary algorithm based on transfer matrix with kriging model (2020)
- Palakonda, Vikas; Mallipeddi, Rammohan: KnEA with ensemble approach for parameter selection for many-objective optimization (2020)
- Qi, Yutao; Liu, Dazhuang; Li, Xiaodong; Lei, Jiaojiao; Xu, Xiaoying; Miao, Qiguang: An adaptive penalty-based boundary intersection method for many-objective optimization problem (2020)
Further publications can be found at: http://dces.essex.ac.uk/staff/zhang/webofmoead.htm