The Evolutionary Computation Methods No One Should Use
Not on the map. Why?
Abstract (arXiv)
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.
Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Builds on 5 of its 103 references that are in the map. First posted on arXiv 5 Jan 2023.
Builds on
5 of 103 references.
References · 5
- 2013Flower Pollination Algorithm for Global Optimizationcited by 11
- 2018Benchmarking Evolutionary Algorithms For Single Objective Real-valued Constrained Optimization - A Critical Reviewcited by 7
- 2015A Social Spider Algorithm for Global Optimizationcited by 4
- 2021Salp Swarm Optimization: a Critical Reviewcited by 3
- 2021Pareto-like Sequential Sampling Heuristic for Global Optimisationcited by 1
Built on by
Citing papers per year: 2025: 2.
2 papers.
- 2025Optimization Problem Solving Can Transition to Evolutionary Agentic Workflowscited by 0
- 2025Taking the GP Out of the Loopcited by 0
- 2025Taking the GP Out of the Loop15 Jun 2025
- 2025Optimization Problem Solving Can Transition to Evolutionary Agentic Workflows7 May 2025