SHAMODE / SHAMODE-WO,

Version 1.0.2 (12.5 KB) by Natee Panagant

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

0.0

(0)

319 Downloads

Updated 24 Sep 2020

View License

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

Cite As

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.

View more styles

MATLAB Release Compatibility

Created with R2018b

Compatible with any release

Platform Compatibility

Windows macOS Linux

Tags Add Tags

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Version	Published	Release Notes
1.0.2	24 Sep 2020	Fix some bugs	Download
1.0.1	22 Jul 2020	Update license file	Download
1.0.0	22 Jul 2020		Download

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} }