2022年9月20日 · Example Gekko and Scipy Optimize Minimize Solutions. GEKKO is a Python package for machine learning and optimization of mixed-integer and differential algebraic equations (see documentation). It is coupled with large-scale solvers for linear, quadratic, nonlinear, and mixed integer programming (LP, QP, NLP, MILP, MINLP).

2021年7月26日 · As I'm pretty new to Gekko and Python itself, and I didn't really found any useful information online, I'm trying to reach anyone with some experience on the Gekko tool that can provide me some guidelines on how to solve DAE problems efficiently or the solution of the problem itself, so I can compare with the unsuccessful trials I already made.

2021年2月18日 · To simulate power flows in grids, I use GEKKO to solve my algebraic differential equation system. For smaller simulations, it works pretty well, but running it several times in a row, for example while training a reinforcement learning agent, takes quite a while.

I tried to convert an example from gekko python optimizer by using the list, array x[] instead of variables x1..x4. This is the code which gives the result, but I think it is not correct This is the code which gives the result, but I think it is not correct

2019年11月26日 · There are two ways to set solver options in Python Gekko with m.options and m.solver_options. Which method takes precedence and when should one or the other be used? For example, I would like to set the objective tolerance (OTOL) and equation residual tolerance (RTOL) for the solver. Which one does Gekko use (1e-7 or 1e-8)?

2019年10月14日 · My goal is to compare the GEKKO‍ performance with an alternative, and so I want to make sure that I'm getting from GEKKO‍ the best it can offer. There are n binary variables, each of them is assigned a weight, each of the weights is a number from the interval [0, 1] (i.e., a rational number w satisfying 0<= w <= 1 ).

The problem is, that when I try and validate these results by using the calculated rate constants to solve the ODEs (with GEKKO or scipy odeint), I get a different result (see figure 1). Points are the measured values, X marks the predicted values, the dashed lines represent the curves that are calculated with odeint using the calculated rate ...

2022年1月18日 · If the compressibility factor needs to change as T1 and x,y change then use Gekko variables so that the model is compiled with that dependency. The functions are only called during problem initialization. Gekko needs the equations with specific Gekko functions to enable automatic differentiation to provide gradients to the solvers.

2022年7月18日 · However, GEKKO runs the function only during initialization. I want GEKKO to solve this task by taking into account that function. It would be really hard to write this function in GEKKOs equations. But without GEKKO it would be really hard to solve the Partial Differential Equations. So I am stuck, I would appreciate any help.

2021年5月7日 · This "indices_open" goes into another self-defined function which is expecting "indices_open" as an numpy array and does not accept a list or gekko-array of gekko-intermediate variables. The self-defined function returns a numpy array. This final array shall be used in m.Equations and I therefore cast it to a gekko variable array.