43 lines
1.4 KiB
Mathematica
43 lines
1.4 KiB
Mathematica
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function P = optimizer(self,x,u)
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%OPTIMIZER Container for optimization problem
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%
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% OPT = OPTIMIZER(Problem,x,u) exports an object that contains
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% precompiled numerical data to be solved for varying arguments
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% x, returning the optimal value of the expression u.
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%
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% SEE OPTIMIZER for more info
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%
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% Example
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%
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% The following problem creates an LP with varying upper and lower
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% bounds on the decision variable.
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%
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% The optimizing argument is obtained by indexing (with {}) the optimizer
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% object with the point of interest. The argument should be a column
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% vector (if the argument has a width larger than 1, YALMIP assumes that
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% the optimal solution should be computed in several points)
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%
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% A = randn(10,3);
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% b = rand(10,1)*19;
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% c = randn(3,1);
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%
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% z = sdpvar(3,1);
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% sdpvar UB LB
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%
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% Constraints = [A*z < b, LB < z < UB];
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% Objective = c'*z;
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% P = optproblem(Constraints,Objective);
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% % We want the optimal z as a function of [LB;UB]
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% optZ = optimizer(P,[LB; UB],z);
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%
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% % Compute the optimal z when LB=1, UB = 3;
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% zopt = optZ{[1; 3]}
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%
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% % Compute two solutions, one for (LB,UB) [1;3] and one for (LB,UB) [2;6]
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% zopt = optZ{[[1; 3], [2;6]]}
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%
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% A second output argument can be used to catch infeasibility
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% [zopt,infeasible] = optZ{[1; 3]}
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P = optimizer(self.Constraints,self.Objective,self.Options,x,u);
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