The DOI matches its Crossref record.
RETRACTED: A hybrid whale optimization algorithm based on local search strategy for the permutation flow shop scheduling problem
Open accessAbstract
Abstract The flow shop scheduling problem is one of the most important types of scheduling with a large number of real-world applications. In this paper, we propose a new algorithm that integrates the Whale Optimization Algorithm (WOA) with a local search strategy for tackling the permutation flow shop scheduling problem. The Largest Rank Value (LRV) requires the algorithm to deal with the discrete search space of the problem. The diversity of candidate schedules is improved using a swap mutation operation as well. In addition to the insert-reversed block operation is adopted to escape from the local optima. The proposed hybrid whale algorithm (HWA) is incorporated with Nawaz–Enscore–Ham (NEH) to improve the performance of the algorithm. It is observed that HWA gives competitive results compared to the existing algorithms.
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
Adaptive Simulation-Based Optimization for Production Scheduling: A Comparative Study
Quadras, D., Frazzon, E. M., Mendes, L. G., Pires, M. C., & Rodriguez, C. M. T. (2022) · IFAC-PapersOnLine · doi:10.1016/j.ifacol.2022.09.430 · Cited by 9
Metadata
- Authors
- Abdel-Basset, M., Manogaran, G., El-Shahat, D., & Mirjalili, S.
- Venue
- Future Generation Computer Systems
- Publisher
- Elsevier BV
- Published
- 2018-08
- Volume
- 85
- Pages
- 129-145
- ISSN
- 0167-739X (ISSN-L)
- OpenAlex
- W2790763152
- Cited by
- 262
- References
- 0
- FWCI
- 38.84
- Type
- journal article
- Language
- en
- Status
- Retracted
- Open access
- green
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: RETRACTED: A hybrid whale optimization algorithm based on local search strategy for the permutation flow shop scheduling problem. https://app.cochat.ai/papers/10.1016/j.future.2018.03.020
- The paper
- Abdel-Basset, M., Manogaran, G., El-Shahat, D., & Mirjalili, S. (2018). RETRACTED: A hybrid whale optimization algorithm based on local search strategy for the permutation flow shop scheduling problem. Future Generation Computer Systems. https://doi.org/10.1016/j.future.2018.03.020
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.
