The DOI matches its Crossref record.
Genetic Algorithms and Engineering Design
Abstract
Foundations of Genetic Algorithms. Constrained Optimization Problems. Combinatorial Optimization Problems. Reliability Optimization Problems. Flow-Shop Sequencing Problems. Job-Shop Scheduling Problems. Machine Scheduling Problems. Transportation Problems. Facility Layout Design Problems. Selected Topics in Engineering Design. Bibliography. Index.
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Citations
Cited by
MOEA/D: A Multiobjective Evolutionary Algorithm Based on Decomposition
Zhang, Q., & Li, H. (2007) · IEEE Transactions on Evolutionary Computation · doi:10.1109/tevc.2007.892759 · Cited by 10,069
Use of a self-adaptive penalty approach for engineering optimization problems
Coello Coello, C. A. (2000) · Computers in Industry · doi:10.1016/s0166-3615(99)00046-9 · Cited by 1,316
An updated survey of GA-based multiobjective optimization techniques
Coello, C. A. (2000) · ACM Computing Surveys · doi:10.1145/358923.358929 · Cited by 773
Comparison of Three Evolutionary Algorithms: GA, PSO, and DE
Kachitvichyanukul, V. (2012) · Industrial Engineering and Management Systems · doi:10.7232/iems.2012.11.3.215 · Cited by 355
Cheng, R., Gen, M., & Tsujimura, Y. (1999) · Computers & Industrial Engineering · doi:10.1016/s0360-8352(99)00022-4 · Cited by 323
Self-citation
Metadata
- Authors
- Gen, M., & Cheng, R.
- Venue
- Wiley eBooks
- Publisher
- Wiley
- Published
- 1996-12-06
- OpenAlex
- W1586313000
- Cited by
- 2,460
- References
- 0
- FWCI
- 13.42
- Type
- book
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: Genetic Algorithms and Engineering Design. https://app.cochat.ai/papers/10.1002/9780470172254
- The paper
- Gen, M., & Cheng, R. (1996). Genetic Algorithms and Engineering Design. Wiley eBooks. https://doi.org/10.1002/9780470172254
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.