Answered: ars Its an genetic algorithm. I would…

Database System Concepts

7th Edition

ISBN:9780078022159

Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Chapter1: Introduction

Section: Chapter Questions

Problem 1PE

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Question

Good afternoon,
Would it be possible for someone to help me to correct this code in matlab unfortunately it is not working a small error appears

Its an genetic algorithm.
I would like to plot a pareto front in 3D with the behavior of the constraints but this error appears.

King Regards

MAIN MATLAB CODE:

% Define decision variables, objectives, and constraints

nvars = 56; % number of decision variables

nobj = 2; % number of objectives

ncon = 44; % number of constraints

% Set up genetic algorithm options

options = optimoptions('ga', ...

'PopulationSize', 100, ...

'MaxGenerations', 100, ...

'MutationFcn', {@mutationuniform, 0.05}, ...

'CrossoverFcn', @crossoverarithmetic);

% Define the objective functions to maximize and minimize

f = @(x) [(Fn/m0)*V0/(1+f+Fab)*((V9^2)/2)-(V0^2)/2, (Fn/m0)*V0/(f*QR*NB), -1-(1/(T1/T0)), m0*V0];

g = @(x) [-f/(Fn/m0), -10^13*p3/(1.4*10^6)*exp(-71442/Tpz)*(7.56*o^7.2-1.6)*(t^0.64), -WT0*(1-WF/WTO-WE/WTO), -(WTO-WLanding), -WT0*(1-WF/WTO-WE/WTO), -M/(TSFC/Fn)];

confun = @(x) deal(myCon1(x), myCon2(x), myCon3(x), myCon4(x), myCon5(x), myCon6(x), myCon7(x), myCon8(x), myCon9(x), myCon10(x), myCon11(x), myCon12(x), myCon13(x), myCon14(x), myCon15(x), myCon16(x), myCon17(x), myCon18(x), myCon19(x), myCon20(x), myCon21(x), myCon22(x), myCon23(x), myCon24(x), myCon25(x), myCon26(x), myCon27(x), myCon28(x), myCon29(x), myCon30(x), myCon31(x), myCon32(x), myCon33(x), myCon34(x), myCon35(x), myCon36(x), myCon37(x), myCon38(x), myCon39(x), myCon40(x), myCon41(x), myCon42(x), myCon43(x), myCon44(x), myCon45(x), myCon46(x), myCon47(x), myCon48(x), myCon49(x), myCon50(x), myCon51(x), myCon52(x), myCon53(x), myCon54(x), myCon55(x) );

% Define your own constraint functions

myCon1 = @(x) f>=1;

myCon2 = @(x) Fn>=1;

myCon3 = @(x) m0>=1;

myCon4 = @(x) p3>=1;

myCon5 = @(x) Tpz>=1;

myCon6 = @(x) o>=1;

myCon7 = @(x) t>=1;

myCon8 = @(x) aa>=1;

myCon9 = @(x) WTO>=1;

myCon10 = @(x) WLanding>=1;

myCon11 = @(x) WF>=1;

myCon12 = @(x) WE>=1;

myCon13 = @(x) WPL>=1;

myCon14 = @(x) WC>=1;

myCon15 = @(x) M>=1;

myCon16 = @(x) Fab>=1;

myCon17 = @(x) V9>=1;

myCon18 = @(x) V0>=1;

myCon19 = @(x) QR>=1;

myCon20 = @(x) NB>=1;

myCon21 = @(x) T1>=1;

myCon22 = @(x) T0>=1;

myCon23 = @(x) L>=1;

myCon24 = @(x) p>=1;

myCon25 = @(x) V>=1;

myCon26 = @(x) A>=1;

myCon27 = @(x) bw>=1;

myCon28 = @(x) sw>=1;

myCon29 = @(x) WZF>=1;

myCon30 = @(x) b>=1;

myCon31 = @(x) cr>=1;

myCon32 = @(x) ct>=1;

myCon33 = @(x) WS>=1;

myCon34 = @(x) RC>=1;

myCon35 = @(x) l>=1;

myCon36 = @(x) m>=1;

myCon37 = @(x) W0>=1;

myCon38 = @(x) VH>=1;

myCon39 = @(x) VS>=1;

myCon40 = @(x) VS1>=1;

% Run genetic algorithm

[x, fval, exitflag, output, population, scores] = ga(objfun, nvars, [], [], [], [], [], [], confun, options);

% Plot Pareto front

pareto(fval(:,1:nobj/2), -fval(:,nobj/2+1:end));

xlabel('Objective 1');

ylabel('Objective 2');

zlabel('Objective 3');

Note this an personal project ,not an assigment !

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