Another update from ingydotnet^djgoku
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Task/Evolutionary-algorithm/MATLAB/evolutionary-algorithm-3.m
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Task/Evolutionary-algorithm/MATLAB/evolutionary-algorithm-3.m
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%% Genetic Algorithm -- Solves For A User Input String
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% #### PLEASE NOTE: you can change the selection and crossover type in the
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% parameters and see how the algorithm changes. ####
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clear;close all;clc; %Clears variables, closes windows, and clears the command window
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tic % Begins the timer
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%% Select Target String
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target = 'METHINKS IT IS LIKE A WEASEL';
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% *Can Be Any String With Any Values and Any Length!*
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% but for this example we use 'METHINKS IT IS LIKE A WEASEL'
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%% Parameters
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popSize = 1000; % Population Size (100-10000 generally produce good results)
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genome = length(target); % Genome Size
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mutRate = .01; % Mutation Rate (5%-25% produce good results)
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S = 4; % Tournament Size (2-6 produce good results)
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best = Inf; % Initialize Best (arbitrarily large)
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MaxVal = max(double(target)); % Max Integer Value Needed
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ideal = double(target); % Convert Target to Integers
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selection = 0; % 0: Tournament
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% 1: 50% Truncation
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crossover = 1; % 0: Uniform crossover
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% 1: 1 point crossover
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% 2: 2 point crossover
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%% Initialize Population
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Pop = round(rand(popSize,genome)*(MaxVal-1)+1); % Creates Population With Corrected Genome Length
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for Gen = 1:1e6 % A Very Large Number Was Chosen, But Shouldn't Be Needed
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%% Fitness
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% The fitness function starts by converting the characters into integers and then
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% subtracting each element of each member of the population from each element of
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% the target string. The function then takes the absolute value of
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% the differences and sums each row and stores the function as a mx1 matrix.
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F = sum(abs(bsxfun(@minus,Pop,ideal)),2);
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% Finding Best Members for Score Keeping and Printing Reasons
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[current,currentGenome] = min(F); % current is the minimum value of the fitness array F
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% currentGenome is the index of that value in the F array
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% Stores New Best Values and Prints New Best Scores
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if current < best
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best = current;
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bestGenome = Pop(currentGenome,:); % Uses that index to find best value
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fprintf('Gen: %d | Fitness: %d | ',Gen, best); % Formatted printing of generation and fitness
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disp(char(bestGenome)); % Best genome so far
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elseif best == 0
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break % Stops program when we are done
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end
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%% Selection
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% TOURNAMENT
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if selection == 0
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T = round(rand(2*popSize,S)*(popSize-1)+1); % Tournaments
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[~,idx] = min(F(T),[],2); % Index to Determine Winners
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W = T(sub2ind(size(T),(1:2*popSize)',idx)); % Winners
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% 50% TRUNCATION
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elseif selection == 1
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[~,V] = sort(F,'descend'); % Sort Fitness in Ascending Order
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V = V(popSize/2+1:end); % Winner Pool
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W = V(round(rand(2*popSize,1)*(popSize/2-1)+1))'; % Winners
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end
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%% Crossover
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% UNIFORM CROSSOVER
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if crossover == 0
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idx = logical(round(rand(size(Pop)))); % Index of Genome from Winner 2
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Pop2 = Pop(W(1:2:end),:); % Set Pop2 = Pop Winners 1
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P2A = Pop(W(2:2:end),:); % Assemble Pop2 Winners 2
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Pop2(idx) = P2A(idx); % Combine Winners 1 and 2
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% 1-POINT CROSSOVER
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elseif crossover == 1
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Pop2 = Pop(W(1:2:end),:); % New Population From Pop 1 Winners
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P2A = Pop(W(2:2:end),:); % Assemble the New Population
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Ref = ones(popSize,1)*(1:genome); % The Reference Matrix
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idx = (round(rand(popSize,1)*(genome-1)+1)*ones(1,genome))>Ref; % Logical Indexing
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Pop2(idx) = P2A(idx); % Recombine Both Parts of Winners
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% 2-POINT CROSSOVER
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elseif crossover == 2
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Pop2 = Pop(W(1:2:end),:); % New Pop is Winners of old Pop
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P2A = Pop(W(2:2:end),:); % Assemble Pop2 Winners 2
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Ref = ones(popSize,1)*(1:genome); % Ones Matrix
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CP = sort(round(rand(popSize,2)*(genome-1)+1),2); % Crossover Points
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idx = CP(:,1)*ones(1,genome)<Ref&CP(:,2)*ones(1,genome)>Ref; % Index
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Pop2(idx)=P2A(idx); % Recombine Winners
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end
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%% Mutation
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idx = rand(size(Pop2))<mutRate; % Index of Mutations
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Pop2(idx) = round(rand([1,sum(sum(idx))])*(MaxVal-1)+1); % Mutated Value
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%% Reset Poplulations
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Pop = Pop2;
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end
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toc % Ends timer and prints elapsed time
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Gen: 1 | Fitness: 465 | C<EFBFBD>I1%G+<%?R<EFBFBD>8>9<EFBFBD>JU#(E<EFBFBD>UO<EFBFBD>PHI
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Gen: 2 | Fitness: 429 | W=P6>D<EFBFBD>I)VU6$T 99,<EFBFBD> B<EFBFBD>BMP0JH
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Gen: 3 | Fitness: 366 | P<EFBFBD>;R08AS<EFBFBD>GJ<EFBFBD>IS&T38IE<EFBFBD>)SJERLJ
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Gen: 4 | Fitness: 322 | KI8M5LAS<EFBFBD>GJ<EFBFBD>IS<EFBFBD>SP<EFBFBD>@)D<EFBFBD>V@
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JCP
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Gen: 5 | Fitness: 295 | UAUR08AS<EFBFBD>GJ<EFBFBD>IS<EFBFBD>8HG*<EFBFBD>+<EFBFBD>=C?UB(
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Gen: 6 | Fitness: 259 | VCUQH35S<EFBFBD>HR4.L<EFBFBD>ISJQ%J<EFBFBD>OC*T=E
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Gen: 7 | Fitness: 226 | LFB8GPET(LODKQ<EFBFBD>KQ<K E*PEMA6I
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Gen: 8 | Fitness: 192 | EPKOLCIR<EFBFBD>QQ<EFBFBD>NF<EFBFBD>QG:B(D/U>BQGF
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Gen: 9 | Fitness: 159 | N8R7?SOU<EFBFBD>NO$OK O?K?!;<EFBFBD>MB?QHG
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Gen: 10 | Fitness: 146 | TGN@EQR4)PS%IS#TFJQ%A!U>BVLI
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Gen: 11 | Fitness: 120 | L?VMALJS%?R EK IILE<EFBFBD>6'RRERLJ
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Gen: 12 | Fitness: 102 | R@T9COMR<EFBFBD>NU CS*R?K?!; VD>LCL
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Gen: 13 | Fitness: 96 | NENMVOMR<EFBFBD>NU CS*R?K?!; VD>LCL
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Gen: 14 | Fitness: 82 | REJGNPMU<EFBFBD>KR CS JKI@+D<EFBFBD>UD?QHG
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Gen: 15 | Fitness: 75 | NETI=HPQ<EFBFBD>FT ID EFKE D"WD>QDQ
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Gen: 16 | Fitness: 70 | R@TKCOOT)@R$IS KKLE<EFBFBD>D"WC?UBJ
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Gen: 17 | Fitness: 61 | NESIKQRP<EFBFBD>NU CS<EFBFBD>MFKE ; SEETCP
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Gen: 18 | Fitness: 57 | LFSGLPTN<EFBFBD>NU GQ IIKE D"VD>LCL
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Gen: 19 | Fitness: 40 | NENKJLMS<EFBFBD>GS%IS#MFKE B UFATCL
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Gen: 21 | Fitness: 39 | NETIGPEU<EFBFBD>KR IS IIKD"? UFDQEK
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Gen: 22 | Fitness: 33 | NETGCOMT<EFBFBD>LU IS#MFKE B UFATCL
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Gen: 23 | Fitness: 32 | NETIKNPQ<EFBFBD>NU IS#IIKE B UFATCL
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Gen: 24 | Fitness: 27 | NETKJLMS<EFBFBD>LU IS MFKE B UFATCL
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Gen: 25 | Fitness: 23 | LETIKOMS LU IS IIKE D WEDQEK
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Gen: 26 | Fitness: 22 | NETIKMJS LU IS IIKE D WEDQEK
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Gen: 27 | Fitness: 20 | LETIKOMS LU IS KILE B"WFATCL
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Gen: 28 | Fitness: 19 | NESGJQJS<EFBFBD>GU IS KIKE B WFATEK
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Gen: 29 | Fitness: 16 | NETIHPMS KR IS KIKE B WFATEK
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Gen: 30 | Fitness: 15 | NESHLPKS KU IS KIKE B WFATEK
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Gen: 31 | Fitness: 13 | NETGGNKS KU IS KIKE C WFATEK
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Gen: 32 | Fitness: 12 | NETHGNJS IU IS JIKE B WFATCL
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Gen: 33 | Fitness: 11 | NETIJPKS IU IS KIKE B WFATEK
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Gen: 35 | Fitness: 8 | LEUIHNJS IT IS JIKE A WEATEL
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Gen: 37 | Fitness: 7 | NETIHNJS IS IS LIKE B WFASEL
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Gen: 38 | Fitness: 6 | NETHGNJS IT IS LIKE A WFASEK
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Gen: 39 | Fitness: 4 | METGHNKS IT IS LIKE B WEATEL
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Gen: 42 | Fitness: 3 | NETHINKS IT IS KIKE B WEASEL
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Gen: 43 | Fitness: 2 | NETHINKS IT IS LIKE A WFASEL
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Gen: 44 | Fitness: 1 | METHHNKS IT IS LIKE A WEASEL
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Gen: 46 | Fitness: 0 | METHINKS IT IS LIKE A WEASEL
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Elapsed time is 0.099618 seconds.
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