Optimizing Biomedical Ontology Alignment through a Compact Multiobjective Particle Swarm Optimization Algorithm Driven by Knee Solution

Algorithm 3

Compact multiobjective particle swarm optimization algorithm driven by knee solution.

	Input: maximum generation , crossover rate , step length for updating
	Output: knee solution
(1)	Initialization
(2)	initialize generation ;
(3)	initialize , and by setting all the elements inside as ;
(4)	initialize three local best individuals , and ;
(5)	generate individuals through , and ;
(6)	;
(7)	initialize the knee solution (or global best individual) ;
(8)	Evolving Process
(9)	while do
(10)	Updating
(11)	generate an individual through ;
(12)
(13)	;
(14)	;
(15)	;
(16)	if then
(17)	= ;
(18)	end if
(19)	Updating
(20)	generate an individual through ;
(21)	= ;
(22)	= ;
(23)
(24)	;
(25)	if winner = =  then
(26)	=  ;
(27)	end if
(28)	Updating
(29)	generate an individual through ;
(30)	= ;
(31)	=  ;
(32)
(33)	;
(34)	if then
(35)	= ;
(36)	end if
(37)	Updating
(38)	generate 2 individuals through , and , respectively,
(39)	;
(40)	determine current generation’s knee solution ;
(41)	;
(42)	if then
(43)	= ;
(44)	end if
(45)	;
(46)	end while
(47)	return ;