基于个体预测的动态多目标优化算法

王万良,陈忠馗,吴菲,王铮,俞梦娇

Dynamic multi-objective optimization algorithm based on individual prediction

Wan-liang WANG,Zhong-kui CHEN,Fei WU,Zheng WANG,Meng-jiao YU

表 4 5种策略在部分测试问题上的MIGD指标

Tab.4 MIGD indicators of five strategies on some test questions

问题	$ ({\tau _t},{n_t}) $	MIGD
问题	$ ({\tau _t},{n_t}) $	PPS	CKPS	SPPS	HPPCM	IPS
FDA2	(20,10)	0.1194(0.00213)‡	0.0087(0.00039)†	0.0097(0.00106)‡	0.0087(0.00908)†	0.0082(0.00034)
	(25,10)	0.0093(0.00120)‡	0.0085(0.00056)‡	0.0087(0.00044)‡	0.0079(0.00087)†	0.0076(0.00075)
	(30,10)	0.0081(0.00046)‡	0.0075(0.00024)†	0.0084(0.00046)‡	0.0072(0.00074)	0.0073(0.00296)
FDA4	(20,10)	0.1485(0.00453)‡	0.1327(0.00086)‡	0.1400(0.04446)‡	0.1094(0.00244)†	0.1082(0.00119)
	(25,10)	0.1314(0.00333)‡	0.1184(0.00230)‡	0.1095(0.00211)‡	0.1020(0.00104)†	0.1010(0.00148)
	(30,10)	0.1221(0.00174)‡	0.1132(0.00066)‡	0.1067(0.00127)‡	0.0962(0.00129)	0.0964(0.00165)
DMOP1	(20,10)	0.1272(0.21435)‡	0.0139(0.00559)‡	0.0148(0.00274)‡	0.0082(0.00175)	0.0084(0.00118)
	(25,10)	0.1296(0.24085)‡	0.0076(0.00174)†	0.0099(0.00276)‡	0.0068(0.00504)†	0.0064(0.00052)
	(30,10)	0.1093(0.19550)‡	0.0060(0.00037)	0.0071(0.00103)†	0.0062(0.00120)†	0.0061(0.00044)
DMOP2	(20,10)	0.0805(0.01495)‡	0.0408(0.00221)†	0.0353(0.00597)	0.0374(0.00724)	0.0384(0.00904)
	(25,10)	0.0659(0.03602)‡	0.0267(0.00616)‡	0.0316(0.00584)‡	0.0252(0.00504)†	0.0223(0.00254)
	(30,10)	0.0391(0.01263)‡	0.0224(0.00188)‡	0.0196(0.00325)†	0.0196(0.00645)†	0.0168(0.00458)
F6	(20,10)	0.1212(0.10641)‡	0.0284(0.00389)†	0.0291(0.00198)†	0.0252(0.00519)†	0.0248(0.00261)
	(25,10)	0.0525(0.02698)‡	0.0210(0.00376)†	0.0219(0.00705)†	0.0189(0.00492)†	0.0188(0.00281)
	(30,10)	0.0432(0.02731)‡	0.0152(0.00167)†	0.0155(0.00201)†	0.0127(0.00207)	0.0142(0.00106)
F9	(20,10)	0.8790(0.27757)‡	0.1495(0.03041)‡	0.2328(0.10508)‡	0.1030(0.01668)†	0.0864(0.01512)
	(25,10)	0.5884(0.20324)‡	0.1476(0.06633)‡	0.1019(0.02075)‡	0.0832(0.03398)†	0.0677(0.01341)
	(30,10)	0.5169(0.16636)‡	0.0872(0.01821)†	0.1089(0.05834)†	0.0658(0.01456)	0.0731(0.02148)