linear programming solver matlab

Operational research and optimal matlab programming Based on Professor Wu qizong's "operational research" and "operational research and optimization methods", the algorithm is implemented by Matlab. If you have any suggestions or requirements, contact me. (Writing is also very tired, AI... if you have time to write ...) Initial directory: Title: Operational Resea

"Matlab Neural network Programming" Chemical Industry Press book notesThe fourth Chapter 4.3 BP propagation Network of forward type neural network This article is "MATLAB Neural network Programming" book reading notes, which involves the source code, formulas, principles are from this book, if there is no understanding

% ====================================================== ===================end Note:caculating the cost function was useful for plotting the figure, but it's not used in gradient descent because the de Rivative'll make the square caculation become mutiply caculation.Gradient descent (for one Variable)By the formula for gradient descent:θj=θj-α* (∂/∂θj (J (θ0, ... ,partθn))) =θj-α* (1/m) *∑i=1~m (hθ (x (i))-Y (i)) *xj (i) (Update θ0 to partθn simultaneously) In Octave, only one line of code co

First, solve the problem Mainly arranges the existing resources (certain), obtains the best benefit the problem solves, moreover the restriction condition is linear. Second, the mathematical model 1. General mathematical model 2. Matlab mathematical model Where c,x are column vectors, A,aeq is a suitable matrix, and b,beq is the appropriate column vector. Then lb and UB are lower and on-line (But note = =

Linux under GLPK (GNU Linear programming Kit) Installation 1.GLPK Introduction The GLPK (GNU Linear programming Kit) package is intended for solving large-scale Linear programming (LP), mixed integer p Rogramming (MIP), and othe

In the previous chapter of the MATLAB compiler did a brief introduction, and introduced how to convert m file into VC callable DLL file, in this chapter describes how to use the compiler to convert m files to the corresponding c\c++ file, and in VC call. The examples in this chapter are the solutions to linear equations that are introduced in the fourth chapter. First, make sure the compiler is set up corr

use of MATLAB. *.4.gradientdescent.mfunction [Theta, j_history] =gradientdescent (X, y, theta, Alpha, num_iters)%gradientdescent performs gradient descent to learn theta% theta = gradientdescent (X, y, theta, Alpha, num_iters) up Dates theta by% taking num_iters gradient steps with learning rate alpha% Initialize Some useful valuesm= Length (y);%Number of training examplesj_history= Zeros (Num_iters,1); forITER =1: Num_iters% ======================

The first step: Enter the target condition and the constraint condition. Each line is separated by semicolons. Then click the Solve button on the toolbar or the Solve submenu under the Lingo menu.Step Two: Check the results in the report.By default, lingo does not perform sensitivity analysis.Need to be configured in lingo to generate a sensitivity analysis report: Lingo menu Options. General Solver tab Dual Computations:prices and Ranges. Then click

imageBW = IM2BW (IOBRCBR, Graythresh (IOBRCBR));Subplot (122); Imshow (BW),Title (' BW ')The background pixel is black, but ideally, we don't want the background marker to be too close to the edge of our target object. We subdivide by ' skeletal ', divide the distance of the two value image, and then look for the boundary of the watershed.%step 11:D = Bwdist (BW);% calculated distanceDL = watershed (D);% Watershed TransformationBGM = DL = = 0;% to find the split boundaryFigure Imshow (BGM),% sh