NAAM-MOEA/D-Based Multitarget Firepower Resource Allocation Optimization in Edge Computing
Algorithm 1
Judgment mechanism of population evolution status.
Input: the threshold ,,; is the attribution judging mechanism of weight vector; is the subproblem evolution degree judgment mechanism; is the population evolution degree judgment mechanism; is the distance between the weight vector and the individual; is the number of individuals owned by the weight vector; represents the number of subproblems with better evolution.
Output: the population evolution state
1 Determine the attribution of the weight vector;
2 for,do
; determine that the individual belongs to the weight vector
else do
3 Calculate the number of individuals owned by the weight vector: ;
4 Determine the degree of evolution of subproblems;
5 for,do
and determine the degree of evolution of subproblems is better
else do;
6 Calculate the number of subproblems with better evolution:
7 Determine the evolution stage of the population;
8 for,do
and determine that the current population evolution degree is too fast, belonging to an overevolution state;
else for,do
and determine that the current population is slowly evolving and belongs to a state of lagging evolution
else for ,do
and determine that the current population has a good evolution speed and belongs to a normal evolutionary state
