A Comparative Study of Fuzzy Logic, Genetic Algorithm, and Gradient-Genetic Algorithm Optimization Methods for Solving the Unit Commitment Problem

<table class="table-group" id="tab3"><tr><td><table class="table"><tr><td class="thead-hr" colspan="9"><hr/></td></tr><tr><td align="left">Hour</td><td align="center">3</td><td align="center">6</td><td align="center">9</td><td align="center">12</td><td align="center">15</td><td align="center">18</td><td align="center">21</td><td align="center">24</td></tr><tr><td align="center" colspan="9"><hr/></td></tr><tr><td align="left">Demand (MW)</td><td align="center">259</td><td align="center">200</td><td align="center">300</td><td align="center">450</td><td align="center">527</td><td align="center">610</td><td align="center">480</td><td align="center">320</td></tr><tr class="table-tr"><td colspan="9"><hr class="tbody-hr"/></td></tr></table></td></tr></table>

Mathematical Problems in Engineering

tab3

Table 3

Table 3: A Comparative Study of Fuzzy Logic, Genetic Algorithm, and Gradient-Genetic Algorithm Optimization Methods for Solving the Unit Commitment Problem 

Table 3 | A Comparative Study of Fuzzy Logic, Genetic Algorithm, and Gradient-Genetic Algorithm Optimization Methods for Solving the Unit Commitment Problem 