Low dimensional simplex evolution (LDSE)
LDSE is a simple but very powerful stochastic optimizer for global optimization. It is a hybrid of downhill simplex and evolutionary algorithm. LDSE has been applied to solve many scientific/engineering problems, and proved very efficient and robust.
A simplified demo of LDSE is shown as follows. You can:
(1) Define your own function to minimize, or select an example to see how to use it.
(2) Set its variable bounds.
(3) Select your parameters.
(4) Click the button "Run LDSE" to see what happens.
A simplified demo of LDSE is shown as follows. You can:
(1) Define your own function to minimize, or select an example to see how to use it.
(2) Set its variable bounds.
(3) Select your parameters.
(4) Click the button "Run LDSE" to see what happens.
References
[1] C.T. Luo and B. Yu, Low dimensional simplex evolution: a hybrid heuristic for global optimization, Journal of Global Optimization, Volume 52, Issue 1 (2012), Page 45-55.
(DOI: 10.1007/s10898-011-9678-1)
[2] C.T. Luo, S.-L. Zhang, B. Yu, Some modifications of low-dimensional simplex evolution and their convergence, Optimization Methods and Software, Volume 28, Number 1, Page 54-81.
(DOI: 10.1080/10556788.2011.584876)
(DOI: 10.1007/s10898-011-9678-1)
[2] C.T. Luo, S.-L. Zhang, B. Yu, Some modifications of low-dimensional simplex evolution and their convergence, Optimization Methods and Software, Volume 28, Number 1, Page 54-81.
(DOI: 10.1080/10556788.2011.584876)