Solving Ontology Metamatching Problem through Improved Multiobjective Particle Swarm Optimization Algorithm

Algorithm 1

The pseudocode of MOPSO-DE.

Input:

 two ontologies and , number of iteration , population size ;

 Particle’s current position , Particle’s current velocity , elite particle set ;

Output:

Winner particle ;

Initialization:

1 initialize generation ;

2 calculate particle’s fitness value and

3 for (; ; ++).

4 =random(0, 1);

5 =random(0, 1);

6 end for.

7 NonDominatedSort()

8 calculateCrowdingDistance();

9 sortFronts();

10 get elite particle set ;

Evolution

11 get elite particle set ;

12  whiledo

13  randomly select two particles and from the elite set ;

14   and of particles and are calculated, respectively;

15  [, ] = compete(, );

16  if and then

17   ;

18  else

19   ;

20  end if.

21  Update:

22   update velocity according to formula (12);

23   update position according to formula (13);

24  update particle’s fitness value and ;

25   = +1;

26 end while

27 return .