Determining starting parameters...
==========
	LC3	LC4	RainLAI	OMLAI8	SIeff8
0:	0.008708	0.000379	0.000473	7.744637	0.676959	=	(	-0.606000	-0.484000	-0.481000	)	-1	1
1:	0.007960	0.009184	0.000489	10.373775	0.665474	=	(	-0.608000	-0.495000	-0.446000	)	-1	2
2:	0.007997	0.002507	0.000339	8.608809	0.654831	=	(	-0.607000	-0.486000	-0.490000	)	-1	3
3:	0.009602	0.002204	0.000083	9.131969	0.615572	=	(	-0.603000	-0.465000	-0.512000	)	-1	4
4:	0.002694	0.009612	0.000439	5.437898	0.781424	=	(	-0.597000	-0.491000	-0.561000	)	-1	5
5:	0.001376	0.008577	0.000058	7.618802	0.430629	=	(	-0.571000	-0.450000	-0.559000	)	-1	6
6:	0.006345	0.005258	0.000232	8.011183	0.434195	=	(	-0.597000	-0.475000	-0.506000	)	-1	7
7:	0.006421	0.003209	0.000495	7.690452	0.420641	=	(	-0.597000	-0.482000	-0.480000	)	-1	8
8:	0.007771	0.004474	0.000441	9.901005	0.730223	=	(	-0.609000	-0.495000	-0.463000	)	-1	9
9:	0.006300	0.007317	0.000101	11.190665	0.742298	=	(	-0.611000	-0.492000	-0.519000	)	-1	10

Results for multi-objective global optimization:
	Needed 0 iterations to solve with a population of 5
==========
	LC3	LC4	RainLAI	OMLAI8	SIeff8	test0	test1	test2 	rank	soln_num

0:	0.0063004	0.0073166	0.00010146	11.191	0.7423	= (	-0.611	-0.492	-0.519 )	1	10
1:	0.0077715	0.0044737	0.00044068	9.901	0.73022	= (	-0.609	-0.495	-0.463 )	1	9
2:	0.0026944	0.0096121	0.00043914	5.4379	0.78142	= (	-0.597	-0.491	-0.561 )	1	5
3:	0.0096025	0.0022041	8.3295e-05	9.132	0.61557	= (	-0.603	-0.465	-0.512 )	2	4
4:	0.0079966	0.0025068	0.00033855	8.6088	0.65483	= (	-0.607	-0.486	-0.49 )	2	3