Simulated annealing: Difference between revisions
Rename Perl 6 -> Raku, alphabetize, minor clean-up
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1</pre>
=={{header|Nim}}==
<lang Nim>import math, random, sugar, strformat
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0</pre>
=={{header|Phix}}==
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#fx(67 68 78 88 98 99 89 79 69 59 49 48 38 39 29 19 9 8 7 17 18 28 27 37 36 26 25 15 16 6 5 4 3 12 13 14 24 34 44 54 53 43 33 23 22 32 31 21 11 2 1 0 10 20 30 40 41 42 52 62 61 51 50 60 70 71 81 80 90 91 92 93 94 84 83 82 72 73 63 64 74 75 65 55 45 35 46 47 58 57 56 66 76 86 85 95 96 97 87 77)
101.65685424949237</pre>
=={{header|Raku}}==
(formerly Perl 6)
{{trans|Go}}
<lang perl6># simulation setup
my \cities = 100; # number of cities
my \kmax = 1e6; # iterations to run
my \kT = 1; # initial 'temperature'
die 'City count must be a perfect square.' if cities.sqrt != cities.sqrt.Int;
# locations of (up to) 8 neighbors, with grid size derived from number of cities
my \gs = cities.sqrt;
my \neighbors = [1, -1, gs, -gs, gs-1, gs+1, -(gs+1), -(gs-1)];
# matrix of distances between cities
my \D = [;];
for 0 ..^ cities² -> \j {
my (\ab, \cd) = (j/cities, j%cities)».Int;
my (\a, \b, \c, \d) = (ab/gs, ab%gs, cd/gs, cd%gs)».Int;
D[ab;cd] = sqrt (a - c)² + (b - d)²
}
sub T(\k, \kmax, \kT) { (1 - k/kmax) × kT } # temperature function, decreases to 0
sub P(\ΔE, \k, \kmax, \kT) { exp( -ΔE / T(k, kmax, kT)) } # probability to move from s to s_next
sub Es(\path) { sum (D[ path[$_]; path[$_+1] ] for 0 ..^ +path-1) } # energy at s, to be minimized
# variation of E, from state s to state s_next
sub delta-E(\s, \u, \v) {
my (\a, \b, \c, \d) = D[s[u-1];s[u]], D[s[u+1];s[u]], D[s[v-1];s[v]], D[s[v+1];s[v]];
my (\na, \nb, \nc, \nd) = D[s[u-1];s[v]], D[s[u+1];s[v]], D[s[v-1];s[u]], D[s[v+1];s[u]];
if v == u+1 { return (na + nd) - (a + d) }
elsif u == v+1 { return (nc + nb) - (c + b) }
else { return (na + nb + nc + nd) - (a + b + c + d) }
}
# E(s0), initial state
my \s = @ = flat 0, (1 ..^ cities).pick(*), 0;
my \E-min-global = my \E-min = $ = Es(s);
for 0 ..^ kmax -> \k {
printf "k:%8u T:%4.1f Es: %3.1f\n" , k, T(k, kmax, kT), Es(s)
if k % (kmax/10) == 0;
# valid candidate cities (exist, adjacent)
my \cv = neighbors[(^8).roll] + s[ my \u = 1 + (^(cities-1)).roll ];
next if cv ≤ 0 or cv ≥ cities or D[s[u];cv] > sqrt(2);
my \v = s[cv];
my \ΔE = delta-E(s, u, v);
if ΔE < 0 or P(ΔE, k, kmax, kT) ≥ rand { # always move if negative
(s[u], s[v]) = (s[v], s[u]);
E-min += ΔE;
E-min-global = E-min if E-min < E-min-global;
}
}
say "\nE(s_final): " ~ E-min-global.fmt('%.1f');
say "Path:\n" ~ s».fmt('%2d').rotor(20,:partial).join: "\n";</lang>
{{out}}
<pre>k: 0 T: 1.0 Es: 522.0
k: 100000 T: 0.9 Es: 185.3
k: 200000 T: 0.8 Es: 166.1
k: 300000 T: 0.7 Es: 174.7
k: 400000 T: 0.6 Es: 146.9
k: 500000 T: 0.5 Es: 140.2
k: 600000 T: 0.4 Es: 127.5
k: 700000 T: 0.3 Es: 115.9
k: 800000 T: 0.2 Es: 111.9
k: 900000 T: 0.1 Es: 109.4
E(s_final): 109.4
Path:
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73 72 71 62 63 64 74 75 65 55 54 53 52 61 51 41 31 21 22 32
42 43 44 45 46 35 34 24 23 33 25 15 16 26 36 47 37 27 17 18
28 38 48 49 39 29 19 9 8 7 6 5 4 14 13 12 11 2 3 1
0</pre>
=={{header|Sidef}}==
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