References in zbMATH (referenced in 274 articles )

1. Chagas, Jonatas B. C.; Wagner, Markus: A weighted-sum method for solving the bi-objective traveling thief problem (2022)
2. Hamada, Naoki; Ichiki, Shunsuke: Free disposal hull condition to verify when efficiency coincides with weak efficiency (2022)
3. Kutlu Onay, Funda; Aydemir, Salih Berkan: Chaotic hunger games search optimization algorithm for global optimization and engineering problems (2022)
4. Luo, Rongjuan; Ji, Shoufeng; Ji, Yuanyuan: An active-learning Pareto evolutionary algorithm for parcel locker network design considering accessibility of customers (2022)
5. Petchrompo, Sanyapong; Wannakrairot, Anupong; Parlikad, Ajith Kumar: Pruning Pareto optimal solutions for multi-objective portfolio asset management (2022)
6. Puertas-Martín, S.; Redondo, J. L.; Ferrández, M. R.; Pérez-Sánchez, H.; Ortigosa, P. M.: MultiPharm-DT: a multi-objective decision tool for ligand-based virtual screening problems (2022)
7. Sahinkoc, H. Mert; Bilge, Ümit: A reference set based many-objective co-evolutionary algorithm with an application to the knapsack problem (2022)
8. von Lücken, Christian; Brizuela, Carlos A.; Barán, Benjamín: Clustering-based multipopulation approaches in MOEA/D for many-objective problems (2022)
9. Ahrari, Ali; Elsayed, Saber; Sarker, Ruhul; Essam, Daryl; Coello Coello, Carlos A.: Weighted pointwise prediction method for dynamic multiobjective optimization (2021)
10. Anghinolfi, Davide; Paolucci, Massimo; Ronco, Roberto: A bi-objective heuristic approach for green identical parallel machine scheduling (2021)
11. Belakaria, Syrine; Deshwal, Aryan; Doppa, Janardhan Rao: Output space entropy search framework for multi-objective Bayesian optimization (2021)
12. Bidgoli, Azam Asilian; Ebrahimpour-Komleh, Hossein; Rahnamayan, Shahryar: Reference-point-based multi-objective optimization algorithm with opposition-based voting scheme for multi-label feature selection (2021)
13. Cosson, Raphaël; Derbel, Bilel; Liefooghe, Arnaud; Aguirre, Hernán; Tanaka, Kiyoshi; Zhang, Qingfu: Decomposition-based multi-objective landscape features and automated algorithm selection (2021)
14. Grimme, Christian; Kerschke, Pascal; Aspar, Pelin; Trautmann, Heike; Preuss, Mike; Deutz, André H.; Wang, Hao; Emmerich, Michael: Peeking beyond peaks: challenges and research potentials of continuous multimodal multi-objective optimization (2021)
15. Huang, Junhao; Sun, Weize; Huang, Lei: Joint structure and parameter optimization of multiobjective sparse neural network (2021)
16. Liagkouras, Konstantinos; Metaxiotis, Konstantinos: Improving multi-objective algorithms performance by emulating behaviors from the human social analogue in candidate solutions (2021)
17. Li, Juan; Xin, Bin; Pardalos, Panos M.; Chen, Jie: Solving bi-objective uncertain stochastic resource allocation problems by the CVaR-based risk measure and decomposition-based multi-objective evolutionary algorithms (2021)
18. Ma, Haiping; Wei, Haoyu; Tian, Ye; Cheng, Ran; Zhang, Xingyi: A multi-stage evolutionary algorithm for multi-objective optimization with complex constraints (2021)
19. Ma, Xuemin; Yang, Jingming; Sun, Hao; Hu, Ziyu; Wei, Lixin: Multiregional co-evolutionary algorithm for dynamic multiobjective optimization (2021)
20. Myszkowski, Paweł B.; Laszczyk, Maciej: Diversity based selection for many-objective evolutionary optimisation problems with constraints (2021)