Paper Info
Title
Benchmarking the Pure Random Search on the Bi-objective BBOB-2016 Testbed.
Abstract
The Comparing Continuous Optimizers platform COCO has become a standard for benchmarking numerical (single-objective) optimization algorithms effortlessly. In 2016, COCO has been extended towards multi-objective optimization by providing a first bi-objective test suite. To provide a baseline, we benchmark a pure random search on this bi-objective family bbob-biobj test suite of the COCO platform. For each combination of function, dimension n, and instance of the test suite, 106 ⋅ n candidate solutions are sampled uniformly within the sampling box [-5,5]n.
Year
DOI
Venue
2016
10.1145/2908961.2931704
GECCO (Companion)
Keywords
Field
DocType
Benchmarking, Black-box optimization, Bi-objective optimization
Test suite,Random search,Mathematical optimization,Computer science,Testbed,Optimization algorithm,Sampling (statistics),Coco,Benchmarking
Conference
Citations 
PageRank 
References 
2
0.41
6
Authors
6
Name
Order
Citations
PageRank
Anne Auger1119877.81
Dimo Brockhoff294853.97
Nikolaus Hansen372351.44
Dejan Tusar4102.34
Tea Tusar518119.91
Tobias Wagner61379.96