Research Article
Composite Differential Search Algorithm
Procedure 1
Algorithm description of Differential search algorithm.
(1) begin | (2) Set the generation counter ; and randomly initialize a population of | NP * individuals . Initialize the parameter , | (3) Evaluate the fitness for each individual in . | (4) while stopping criteria is not satisfied do | (5) scale = randg(2 * rand) * (rand-rand) | (6) for to NP do | (7) select randomly | (8) | (9) end | (10) = rand (NP, ); | (11) If rand < rand then | (12) If rand < then | (13) for = 1 to NP do | (14) (,:) = (,:) < rand | (15) end | (16) else | (17) for = 1 to NP do | (18) (, randi()) = 0 | (19) end | (20) end | (21) else | (22) for = 1 to NP do | (23) = randi(, 1, ) | (24) for = 1 to size (, 2) do | (25) (, ()) = 0 | (26) end | (27) end | (28) end | (29) ; | (30) ; | (31) for to NP do | (32) Evaluate the offspring | (33) If is better than then | (34) | (35) end if | (36) end for | (37) Memorize the best solution achieved so far | (38) end while | (39) end |
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