Research Article
Goal-Programming-Driven Genetic Algorithm Model for Wireless Access Point Deployment Optimization
Table 9
Analysis of the results of Experiment 3.
| | Indicator | Fixed mutation rate () | Fixed crossover rate () | | | | | |
| | Fitness | 1 (.9869) | 1 () | 1 () | 1 () | 1 () | | Generation | 96 (93) | 53 (86) | 18 (26) | 9 (94) | 22 (62) | | Time | 489.2550
(3795.2) | 526.2310
(5080.5) | 552.5640
(3880.6) | 496.0540
(3334.8) | 541.5390
(4866.5) | | Cost | 1,349,670
(5,736,480) | 1,326,549
(5,593,797) | 1,347,933
(5,576,205) | 1,348,896
(5,580,897) | 1,324,479
(5,566,053) | | Capacity fulfillment rate | .8485
(.8641) | .8384
(.8536) | .8495
(.8486) | .8450
(.8502) | .8531
(.8560) | | Coverage fulfillment rate | .8500
(.8536) | .8496
(.8634) | .8484
(.8506) | .8496
(.8510) | .8496
(.8559) | | Interference | .8996
(.8929) | .9100
(.8914) | .8996
(.8891) | .9048
(.8987) | .9012
(.8952) |
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The experiment results for E3(b) are in parentheses.
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