http://youtube.com/watch?v=bd43rrHmsx0使用Matlab中的fminunc解决Rosenbrock问题的快速示例,Rosenbrock问题是经典的无约束优化测试问题。代码:https://github.com/abe-mart/alphaopt/blob/master/rosenbrock.m, 视频播放量 694、弹幕量 0、点赞数 5、投硬币枚数 0、收藏
After an introduction to main ideas of semi-infinite optimization, this article surveys recent developments in theory and numerical methods for standard and generalized semi-infinite optimization problems. Particular attention is paid to connections with mathematical programs with complementarity constraints, ...
functions. lsqnonlin exploits the inherent structure in a least-squares problem and uses it to ...
O. Stein, "How to solve a semi-infinite optimization problem," Euro- pean Journal of Operational Research, vol. 223, no. 2, pp. 312-320, 2012.Oliver;Stein.How to solve a semi-infinite optimization problem.European Journal of Operational Research.2012...
My optimization problem is very long, but the problem is at line 142 , => i.e, for i = 1:N power(h_cvx ,2) + power(x_cvx - position(i,1) ,2) + power (y_cvx(3) - position(i,2) ,2) - u_cvx<= 0; Here is the error I got: ...
There are just too many ways to solve them One thing is for sure — There are too many ways to solve convex optimization tasks. By "too many", I mean, at least a dozen. We can't cover all of them here! So, I will be covering the methods that can be used in a majority of co...
Using these techniques, it's possible to significantly improve the experience of the end users of a cloud application to solve the peculiar problem of a long tail. References Li, J., Sharma, N. K., Ports, D. R., & Gribble, S. D. (2014).Tales of the Tail: Hardware, OS, and App...
If someone can help my problem, I will very much appreciate him/her. I want to minimize an objective function which is condition number of a matrix W having many rows and each row having time-dependent variables. It is a problem in robotics. I have an observati...
Could you tell me which solver is the best to be used for this optimization? Besides, I don't have an initial matrix (point), X0, to start from. What should I do?
To solve the constrained optimization problem, we employed the real-coded genetic algorithm (GA) named IS-SR-REXstar/JGG (see Section 4.3 of Supplementary Information). We performed the parameter estimation on the supercomputer Shirokane3. A single run for the parameter estimation took 12 h ...