Research Article

Multiobjective Optimization of Allocated Exchange Portfolio: Model and Solution—A Case Study in Iran

Table 10

Results of WGC method with assumption .

Set

110.90.00010.09990.02889978000.02957703000.9415892000.00004272890.00017204070.2783438020
20.90.010.09000.0704336100.0627853600.8667810000.00006302360.00019164650.2612935966
30.90.020.08000.1010062000.1742378000.7247559000.00009393320.00021599250.2309966359
40.90.030.07000.1164281000.2782165000.6053554000.00011400420.00023681190.2025025916
50.90.040.06000.1237514000.3772991000.4989495000.00012456070.00025558500.1752216400
60.90.050.05000.1251134000.4732183000.4016683000.00012646840.00027293070.1487117233
70.90.060.04000.1211891000.5675009000.3113100000.00012031310.00028921940.1225622706
80.90.070.03000.1117466000.6618317000.2264217000.00010646380.00030471890.0963031761
90.90.080.02000.0953421600.7586449000.1460130000.00008507840.00031965570.0692358501
100.90.090.01000.0669681400.8633145000.0697173300.00005603110.00033426640.0397864172
110.90.09990.000100.0405752500.95942480000.00002713180.0003459004–0.007842553

2120.80.00010.19990.05471173000.05863598000.8866523000.00007046640.00017405080.2792061779
130.80.020.18000.1133953000.0609554000.8256493000.00011520600.00019753080.2625496001
140.80.040.16000.1522089000.1668948000.6808963000.00018072550.00022208280.2339214799
150.80.060.14000.1723754000.2648067000.5628179000.00022275320.00024250350.2071885246
160.80.080.12000.1819712000.3579865000.4600423000.00024472310.00026054980.1815800991
170.80.10.1000.1836426000.4486486000.3677088000.00024870240.00027700030.1565298298
530.50.40.1000.2721378000.6415025000.0863597000.00052501730.00032427420.1047260381
540.50.450.05000.2073034000.7598740000.0328226500.00031677910.00033606310.0708499014
550.50.49990.000100.00498606100.99501390000.00002807790.0003486375–0.000255917

6560.40.00010.59990.13414220000.14826150000.7175963000.00027855190.00018023650.2818599514
570.40.060.54000.2700789000.0542814400.6756396000.00051751790.00021899140.2671303981
580.40.120.48000.3433666000.1394806000.5171528000.00081843420.00024481970.2448411970
870.20.720.08000.3321500000.66785000000.00077223690.00033766150.0984850362
880.20.79990.000100.00125999100.99874000000.00002818450.00034892410.0005383473

9890.10.00010.89990.26761180000.29886190000.4335263000.00104538940.00019063060.2863191600
900.10.090.81000.5562134000.0420935100.4016931000.00211093160.00025818260.2754957253
910.10.180.72000.6683496000.0928743000.2387761000.00303829420.00028347430.2634055738
920.10.270.63000.7203725000.1334595000.1461679000.00352700490.00029825190.2530866771
930.10.360.54000.7435903000.1716868000.0847228100.00375746720.00030844320.2429172472
940.10.450.45000.7475166000.2119432000.0405402500.00379790280.00031620800.2318497581
950.10.540.36000.7344771000.2583218000.0072010890.00366827090.00032261440.2187927134
960.10.630.27000.6573371000.34266290000.00294379680.00032654010.1941155015
970.10.720.18000.5280837000.47191630000.00190968110.00033096050.1561048830
980.10.810.09000.3321500000.66785000000.00077223690.00033766150.0984850362
990.10.89990.000100.00056112600.99943890000.00002820470.00034897790.0006872967

Remark: negative values of column are costs and positive values are incomes.