NAAM-MOEA/D-Based Multitarget Firepower Resource Allocation Optimization in Edge Computing

Algorithm 3

The framework of NAAM-MOEA/D algorithm.

Input: optimal model of multiobjective fire resource allocation; termination criteria; population size ; population crossover probability ; probability of population variation ;

Output: optimal plan for firepower resource allocation

1 Initialize

2 

3 Initialize population individuals ;

4 Generate weight vector , ,…, ;

5 Calculate the Euclidean distance between any two weight vectors. For each weight vector, find the nearest weight vectors to form its neighborhood. and . Among them, ,,…, are the weight vectors closest to ;

6 Initialize the ideal point ;

7 Evolution

8 for, do

9   Crossover and mutation: randomly select two individuals in to perform crossover and mutation operations to obtain offspring individual ;

10   Update ideal point

11   for each.

   if, then

      end

12   Set adaptive neighborhood

13   Judge the subproblems and the evolution status of the population through the criteria provided in Section 2.1;

14   Use the method provided in Section 2.2 to obtain the population neighborhood and the neighborhood corresponding to the subproblem;

15   Update neighborhood

     for each

       if then

        ,

       end

     end

16   Remove all individuals dominated by in and add individuals not dominated to at the same time;

17 end

18 Stop operation

19 After the algorithm evolves to the maximum algebra , it stops and outputs the optimal solution. If the stopping condition is not met, it returns to Step 7.