The DOI matches its Crossref record; 16 of the 16 references it cites were found in a registry or an index.
Multiobjective optimization using a Pareto differential evolution approach
Abstract
Differential evolution is a simple, fast, and robust evolutionary algorithm that has proven effective in determining the global optimum for several difficult single-objective optimization problems. In this paper, the differential evolution algorithm is extended to multiobjective optimization problems by using a Pareto-based approach. The algorithm performs well when applied to several test optimization problems from the literature.
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Citations
Cites
A fast and elitist multiobjective genetic algorithm: NSGA-II
Deb, K., Pratap, A., Agarwal, S., & Meyarivan, T. (2002) · IEEE Transactions on Evolutionary Computation · doi:10.1109/4235.996017 · Cited by 50,053
Multi-Objective Optimization Using Evolutionary Algorithms
Deb, K., & Kalyanmoy, D. (2001) · Andalas University Repository (Andalas University) · Cited by 14,918
Muiltiobjective Optimization Using Nondominated Sorting in Genetic Algorithms
Srinivas, N., & Deb, K. (1994) · Evolutionary Computation · doi:10.1162/evco.1994.2.3.221 · Cited by 6,935
A Fast Elitist Non-dominated Sorting Genetic Algorithm for Multi-objective Optimization: NSGA-II
Deb, K., Agrawal, S., Pratap, A., & Meyarivan, T. (2000) · Lecture Notes in Computer Science · doi:10.1007/3-540-45356-3_83 · Cited by 5,289
A niched Pareto genetic algorithm for multiobjective optimization
Horn, J., Nafpliotis, N., & Goldberg, D. E. (2002) · Proceedings of the First IEEE Conference on Evolutionary Computation. IEEE World Congress on Computational Intelligence · doi:10.1109/icec.1994.350037 · Cited by 2,433
An Overview of Evolutionary Algorithms in Multiobjective Optimization
Fonseca, C. M., & Fleming, P. J. (1995) · Evolutionary Computation · doi:10.1162/evco.1995.3.1.1 · Cited by 2,266
Evolutionary computation: Comments on the history and current state
Back, T., Hammel, U., & Schwefel, H.-P. (1997) · IEEE Transactions on Evolutionary Computation · doi:10.1109/4235.585888 · Cited by 1,536
A Comprehensive Survey of Evolutionary-Based Multiobjective Optimization Techniques
Coello Coello, C. A. (1999) · Knowledge and Information Systems · doi:10.1007/bf03325101 · Cited by 1,367
Knowles, J., & Corne, D. (2003) · Proceedings of the 1999 Congress on Evolutionary Computation-CEC99 (Cat. No. 99TH8406) · doi:10.1109/cec.1999.781913 · Cited by 1,278
Multiobjective evolutionary algorithms: classifications, analyses, and new innovations
Lamont, G. B., & Veldhuizen, D. A. V. (1999) · Cited by 1,212
Cited by
Multiobjective firefly algorithm for continuous optimization
Yang, X.-S. (2013) · Engineering with Computers · doi:10.1007/s00366-012-0254-1 · Cited by 513
Solving Rotated Multi-objective Optimization Problems Using Differential Evolution
Iorio, A. W., & Li, X. (2004) · Lecture Notes in Computer Science · doi:10.1007/978-3-540-30549-1_74 · Cited by 263
Ali, M., Siarry, P., & Pant, M. (2011) · European Journal of Operational Research · doi:10.1016/j.ejor.2011.09.025 · Cited by 254
Metadata
- Authors
- Madavan, N. K.
- Venue
- Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600)
- Publisher
- IEEE
- Published
- 2003-06-25
- Volume
- 2
- Pages
- 1145-1150
- OpenAlex
- W1554486237
- Cited by
- 275
- References
- 16
- FWCI
- 6.28
- Type
- conference paper
- Language
- en
- Open access
- closed
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- Madavan, N. K. (2003). Multiobjective optimization using a Pareto differential evolution approach. Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600). https://doi.org/10.1109/cec.2002.1004404
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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.
