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Adaptive differential evolution algorithm with novel mutation strategies in multiple sub-populations

Cui, Laizhong; Cui, Laizhong; Lin, Qiuzhen; Chen, Jianyong - In: Computers & operations research : and their … 67 (2016), pp. 155-173

Persistent link: https://www.econbiz.de/10011441316

A novel differential evolution algorithm using local abstract convex underestimate strategy for global optimization

Zhou, Xiao-gen; Zhang, Gui-jun; Hao, Xiao-hu; Yu, Li - In: Computers & operations research : and their … 75 (2016), pp. 132-149

Persistent link: https://www.econbiz.de/10011544993

Efficient large scale global optimization through clustering-based population methods

Schoen, Fabio; Tigli, Luca - In: Computers & operations research : and their … 127 (2021), pp. 1-15

Persistent link: https://www.econbiz.de/10012432325

Low dimensional simplex evolution: a new heuristic for global optimization

Luo, Changtong; Yu, Bo - In: Journal of Global Optimization 52 (2012) 1, pp. 45-55

Persistent link: https://www.econbiz.de/10009399896

Performance of Differential Evolution and Particle Swarm Methods on Some Relatively Harder Multi-modal Benchmark Functions

Mishra, SK - Volkswirtschaftliche Fakultät, … - 2006

Our objective in this paper is to compare the performance of the Differential Evolution (DE) and the Repulsive Particle Swarm (RPS) methods of global optimization. To this end, some relatively difficult test functions have been chosen. These functions are: Perm, Power-Sum, Bukin, Zero-Sum,...

Persistent link: https://www.econbiz.de/10005835442