The Evolutionary Computation Methods No One Should Use
This addresses a critical benchmarking flaw for researchers in evolutionary computation, though it is incremental in identifying and quantifying an existing problem rather than proposing a new solution.
The paper tackled the problem of center-bias in evolutionary computation methods, which skews benchmarking by favoring functions with optima at the center, and found that over half (47 out of 90) of methods published from 1987 to 2022 have this issue, with it becoming prevalent since 2012.
The center-bias (or zero-bias) operator has recently been identified as one of the problems plaguing the benchmarking of evolutionary computation methods. This operator lets the methods that utilize it easily optimize functions that have their respective optima in the center of the feasible set. In this paper, we describe a simple procedure that can be used to identify methods that incorporate a center-bias operator and use it to investigate 90 evolutionary computation methods that were published between 1987 and 2022. We show that more than half (47 out of the 90) of the considered methods have the center-bias problem. We also show that the center-bias is a relatively new phenomenon (with the first identified method being from 2012), but its inclusion has become extremely prevalent in the last few years. Lastly, we briefly discuss the possible root causes of this issue.