mathematical-optimization

问题 I am still very new to Python, after years and years of Matlab. I am trying to use Pulp to set up an integer linear program. Given an array of numbers: {P[i]:i=1...N} I want to maximize: sum( x_i P_i ) subject to the constraints A x <= b A_eq x = b_eq and with bounds (vector based bounds) LB <= x <= UB In pulp however, I don't see how to do vector declarations properly. I was using: RANGE = range(numpy.size(P)) x = pulp.LpVariable.dicts("x", LB_ind, UB_ind, "Integer") where I can only enter

问题 I have been using the Excel solver to handle the following problem solve for a b and c in the equation: y = a*b*c*x/((1 - c*x)(1 - c*x + b*c*x)) subject to the constraints 0 < a < 100 0 < b < 100 0 < c < 100 f(x[1]) < 10 f(x[2]) > 20 f(x[3]) < 40 where I have about 10 (x,y) value pairs. I minimize the sum of abs(y - f(x)). And I can constrain both the coefficients and the range of values for the result of my function at each x. I tried nls (without trying to impose the constraints) and while

问题 I have 3 receivers (A, B and C), and some signal producing source (let's say sound or light) with an unknown location. Given the locations of A,B and C, and the time at which each receiver "heard" the signal, I'd like to determine the direction of the source. I understand there are ways to do so with TDoA multilateration/trilateration, however I'm having trouble implementing the calculation. There isn't a lot of clear, detailed information on this out there for those entirely new to the

问题 I have 3 receivers (A, B and C), and some signal producing source (let's say sound or light) with an unknown location. Given the locations of A,B and C, and the time at which each receiver "heard" the signal, I'd like to determine the direction of the source. I understand there are ways to do so with TDoA multilateration/trilateration, however I'm having trouble implementing the calculation. There isn't a lot of clear, detailed information on this out there for those entirely new to the

来源： https://stackoverflow.com/questions/64634808/optimization-solve-for-an-input-value-given-a-known-output-value-in-r

来源： https://stackoverflow.com/questions/64634808/optimization-solve-for-an-input-value-given-a-known-output-value-in-r

来源： https://stackoverflow.com/questions/35432478/scipy-minimize-constrained-function

来源： https://stackoverflow.com/questions/12356041/is-normalization-useful-necessary-in-optimization

来源： https://stackoverflow.com/questions/63413064/how-to-build-hybrid-model-to-find-optimal-discount-of-products

来源： https://stackoverflow.com/questions/58646404/how-to-solve-absolute-value-abs-objective-with-python-gekko