The DOI matches its Crossref record.
An overview of evolutionary algorithms: practical issues and common pitfalls
Abstract
Abstract An overview of evolutionary algorithms is presented covering genetic algorithms, evolution strategies, genetic programming and evolutionary programming. The schema theorem is reviewed and critiqued. Gray codes, bit representations and real-valued representations are discussed for parameter optimization problems. Parallel Island models are also reviewed, and the evaluation of evolutionary algorithms is discussed.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cited by
Search‐based software test data generation: a survey
McMinn, P. (2004) · Software Testing, Verification and Reliability · doi:10.1002/stvr.294 · Cited by 1,368
Search-based software engineering
Harman, M., & Jones, B. F. (2001) · Information and Software Technology · doi:10.1016/s0950-5849(01)00189-6 · Cited by 914
Variable selection in regression—a tutorial
Andersen, C. M., & Bro, R. (2010) · Journal of Chemometrics · doi:10.1002/cem.1360 · Cited by 697
Evolutionary algorithms: A critical review and its future prospects
Vikhar, P. A. (2016) · 2016 International Conference on Global Trends in Signal Processing, Information Computing and Communication (ICGTSPICC) · doi:10.1109/icgtspicc.2016.7955308 · Cited by 486
Discovery and Optimization of Materials Using Evolutionary Approaches
Le, T. C., & Winkler, D. A. (2016) · Chemical Reviews · doi:10.1021/acs.chemrev.5b00691 · Cited by 204
Metadata
- Authors
- Whitley, D.
- Venue
- Information and Software Technology
- Publisher
- Elsevier BV
- Published
- 2001-12
- Volume
- 43
- Issue
- 14
- Pages
- 817-831
- ISSN
- 0950-5849 (ISSN-L)
- OpenAlex
- W2024425422
- Cited by
- 448
- References
- 0
- FWCI
- 8.64
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: An overview of evolutionary algorithms: practical issues and common pitfalls. https://app.cochat.ai/papers/10.1016/s0950-5849(01)00188-4
- The paper
- Whitley, D. (2001). An overview of evolutionary algorithms: practical issues and common pitfalls. Information and Software Technology. https://doi.org/10.1016/s0950-5849(01)00188-4
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
