The Opposition-Based Learning Parameter Adjusting Harmony Search Algorithm Research on Radars Optimal Deployment

Table 14

Comparison of two maps distribution character.

Iterations	Five radars’ coordinates (m)	Fitness
1	(67200,30400),(68200,41800),(70200,70600),(35600,45000),(3000,17800)	0.2156
22	(34000,23400),(31200,8400),(49600,42800),(63400,41000),(47800,45800)	0.2361
50	(60000,30400),(31200,31000),(49600,42800),(26000,60000),(21200,45800)	0.3519
106	(43600,30400),(31200,56600),(,49600,46200),(47400,60000),(67200,42000)	0.3533
118	(54600,30400),(31200, 31000),(49600,55800),(2600050600),(67200,42000)	0.3674
135	(54600,30400),(31200,49600),(49600,42800),(47400,60000),(67200,42000)	0.3834
180	(54200,30400),(34200,31000),(49600,42800),(63400,50600),(67200,45800)	0.4100
293	(54600,30400),(34200,30800),(49600,42800),(63400,50600),(67200,45800)	0.4119
385	(61000,30400),(34200,31000),(49600,44400),(63400,50600),(67200,63600)	0.4165
406	(54200,30400),(34200,30800), (49600,48600),(63400,50600),(67200,42000)	0.4196
423	(54200,30400),(34200,30800),(49600,48600),(63400,50600),(67200,33600)	0.4241
480	(54200,30400),(34200,30800),(49600,49000),(63400,50600),(67200,33800)	0.4253
562	(54200,30400),(34200,30800),(38000,48600),(63400,50600),(67200,33600)	0.4293