A Selection Hyper-Heuristic Algorithm for Multiobjective Dynamic Economic and Environmental Load Dispatch

Table 4

Optimal compromise results for Case 1.

H	P1	P2	P3	P4	P5	PL	Ec ($)	Em (lb)
1	60.68	65.18	112.89	124.70	50.07	3.51	1461.20	362.60
2	63.25	78.87	112.39	125.02	59.42	3.95	1538.25	396.97
3	72.17	81.73	117.52	124.93	83.33	4.67	1738.45	453.15
4	75.00	90.54	127.86	126.08	116.32	5.80	1838.91	557.48
5	74.99	97.06	132.76	126.87	132.76	6.43	1798.62	624.45
6	74.99	98.37	160.99	141.66	139.61	7.62	2000.13	730.30
7	75.00	98.21	160.02	169.65	131.22	8.11	2178.50	761.97
8	75.00	98.51	163.85	187.80	137.71	8.87	2144.33	837.33
9	75.00	100.43	174.97	209.76	139.77	9.91	2062.54	945.48
10	75.00	114.67	175.00	209.79	139.90	10.36	2172.01	986.93
11	75.00	125.00	175.00	210.00	145.86	10.86	2292.06	1040.11
12	75.00	125.00	175.00	214.67	161.79	11.46	2467.32	1109.97
13	75.00	114.34	174.98	209.80	140.24	10.36	2172.79	986.88
14	75.00	100.26	175.00	209.82	139.84	9.91	2061.54	945.54
15	75.00	98.40	165.56	184.52	139.39	8.86	2143.03	837.42
16	75.00	98.43	145.18	134.52	133.82	6.94	1926.89	665.95
17	74.81	97.49	134.45	125.36	132.33	6.43	1797.18	624.51
18	74.98	98.53	162.28	140.16	139.67	7.62	1988.62	731.37
19	75.00	98.48	166.20	185.63	137.55	8.86	2149.55	836.91
20	75.00	114.74	175.00	209.85	139.76	10.36	2171.44	986.96
21	74.39	98.34	174.96	202.34	139.58	9.61	2080.14	914.34
22	74.99	98.50	146.73	152.80	139.54	7.56	2039.88	719.77
23	74.91	98.19	114.13	125.80	119.74	5.77	1691.22	564.86
24	67.58	92.99	112.66	124.32	69.93	4.49	1588.60	444.58
Total						188.35	47503	18066