SHAMODE / SHAMODE-WO,

Version 1.0.2 (12,5 ko) par Natee Panagant

Success History–based Adaptive Multi-Objective Differential Evolution (SHAMODE) and the Whale Optimization hybrid version (SHAMODE-WO)

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Two constrained multiobjective metaheuristics are presented.
1) Success History–based Adaptive Multi-Objective Differential Evolution (SHAMODE) is an improved multiobjective version of Success History-based Adaptive Differential Evolution (SHADE) by integrating modified adaptive strategies and non-dominated sorting algorithm.
2) Success History–based Adaptive Multi-Objective Differential Evolution with Whale Optimization (SHAMODE-WO) is an improved multiobjective version of Success History-based Adaptive Differential Evolution (SHADE) by integrating modified adaptive strategies, non-dominated sorting algorithm, and additional population update operator from Whale Optimization Algorithm (WOA).

The algorithms are published in:
Panagant, N., Bureerat, S., & Tai, K. (2019). A novel self-adaptive hybrid multi-objective meta-heuristic for reliability design of trusses with simultaneous topology, shape and sizing optimisation design variables. Structural and Multidisciplinary Optimization, 60(5), 1937-1955. DOI: https://doi.org/10.1007/s00158-019-02302-x

Citation pour cette source

Panagant, Natee, et al. “A Novel Self-Adaptive Hybrid Multi-Objective Meta-Heuristic for Reliability Design of Trusses with Simultaneous Topology, Shape and Sizing Optimisation Design Variables.” Structural and Multidisciplinary Optimization, vol. 60, no. 5, Springer Science and Business Media LLC, June 2019, pp. 1937–55, doi:10.1007/s00158-019-02302-x.

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Version	Publié le	Notes de version
1.0.2	24 sept. 2020	Fix some bugs	Télécharger
1.0.1	22 juil. 2020	Update license file	Télécharger
1.0.0	22 juil. 2020		Télécharger

MLA	Panagant, Natee, et al. “A Novel Self-Adaptive Hybrid Multi-Objective Meta-Heuristic for Reliability Design of Trusses with Simultaneous Topology, Shape and Sizing Optimisation Design Variables.” Structural and Multidisciplinary Optimization, vol. 60, no. 5, Springer Science and Business Media LLC, June 2019, pp. 1937–55, doi:10.1007/s00158-019-02302-x.
APA	Panagant, N., Bureerat, S., & Tai, K. (2019). A novel self-adaptive hybrid multi-objective meta-heuristic for reliability design of trusses with simultaneous topology, shape and sizing optimisation design variables. Structural and Multidisciplinary Optimization, 60(5), 1937–1955. Springer Science and Business Media LLC. Retrieved from https://doi.org/10.1007%2Fs00158-019-02302-x
BibTeX	@article{Panagant_2019, doi = {10.1007/s00158-019-02302-x}, url = {https://doi.org/10.1007%2Fs00158-019-02302-x}, year = 2019, month = {jun}, publisher = {Springer Science and Business Media {LLC}}, volume = {60}, number = {5}, pages = {1937--1955}, author = {Natee Panagant and Sujin Bureerat and Kang Tai}, title = {A novel self-adaptive hybrid multi-objective meta-heuristic for reliability design of trusses with simultaneous topology, shape and sizing optimisation design variables}, journal = {Structural and Multidisciplinary Optimization} }