COCO

COCO (COmparing Continuous Optimisers) is a platform for systematic and sound comparisons of real-parameter global optimisers. COCO provides benchmark function testbeds, experimentation templates which are easy to parallelize, and tools for processing and visualizing data generated by one or several optimizers.

Keywords for this software

Anything in here will be replaced on browsers that support the canvas element

References in zbMATH (referenced in 3 articles )

Showing results 1 to 3 of 3.
Sorted by year (citations)

  1. Xiang, Yi; Peng, Yuming; Zhong, Yubin; Chen, Zhenyu; Lu, Xuwen; Zhong, Xuejun: A particle swarm inspired multi-elitist artificial bee colony algorithm for real-parameter optimization (2014)
  2. Ahrari, Ali: A requirement for the mutation operator in continuous optimization (2013)
  3. Korošec, Peter; Šilc, Jurij: The continuous differential ant-stigmergy algorithm for numerical optimization (2013)