Differential Evolution for Lifetime Maximization of Heterogeneous Wireless Sensor Networks

Pseudocode 3

The pseudocode of proposed DEDSC algorithm. Note that the pseudo code is described by Matlab language, and the bold words are inner functions or keywords in Matlab.

/* proposed DEDSC algorithm */

(1) Load test data set.

(2) Initialization parameters 𝐹,𝐶_𝑟, et. al

   % Initialization population

(3) popold=  round(unifrnd(1, 𝐶_max, popsize, m));

(4) Recombination operation

(5) FES=0; % the generation of evolution

(6) while FES<𝑚∗100

(7) pop=popold;

(8) 𝑣_𝑖,𝑔=𝑥_𝑟1,𝑔+𝐹_𝑖⋅(𝑥_𝑟2,𝑔−𝑥_𝑟3,𝑔)  % mutation

(9) for  𝑖= 1: popsize

(10)    for  𝑗= 1: 𝑚

     𝑣_𝑖,𝑔(𝑗)=  ceil (𝑣_𝑖,𝑔(𝑗)); % round numbers

(11)    if  𝑣_𝑖,𝑔(𝑗)<1or𝑣_𝑖,𝑔(𝑗)>𝐶_max  % boundary

      checkout

        % regenerate a random integer

        % between [1,𝐶_max] to update 𝑣_𝑖,𝑔(𝑗)

(12)      𝑣_𝑖,𝑔(𝑗)= randint(1,1,[1, 𝐶_max]);

(13)    end

(14)   end

(15) end

(16) Crossover between 𝑣_𝑖,𝑔 and 𝑥_𝑖,𝑔 by (5)

     % Evaluate fitness for 𝑥_𝑖,𝑔 and 𝑢_𝑖,𝑔

(17) for  𝑖= 1: popsize % for each chromosome 𝑖

(18)  for  𝑗= 1: 𝐶_max

(19)   find those sensors with same subset index 𝑗.

(20)   for every sensors 𝑘.

(21)    count each 𝑘 cover the targets and

      union them.

(22)   end

(23)   if the number of targets 𝑧 is equal 𝑛

(24)     this subset 𝑗 can complete coverage;

(25)   else

(26)     this subset 𝑗 coverage percentage is 𝑧/𝑛;

(27)   end

(28)  end

(29)  count fitness of chromosome 𝑖 by (1);

(30)  end

(31) Selection operation by (6);

(32) Update popold;

(33) FES=FES+popsize;  % next generation

   % Judgment of terminal condition

(34) if  FES≥𝑚∗100  or the best fitness equals 𝐶_max

(35)  break;

(36) end

(37) end