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="tab4"><tr><td><table class="table"><tr><td class="thead-hr" colspan="4"><hr/></td></tr><tr class="thead"><td align="left"> </td><td align="center">Genetic algorithm</td><td align="center">Fuzzy logic</td><td align="center">Gradient-genetic algorithm</td></tr><tr><td class="thead-hr" colspan="4"><hr/></td></tr><tr><td align="left">Production cost ($)</td><td align="center">29457</td><td align="center">29210</td><td align="center">27750</td></tr><tr class="table-tr"><td colspan="4"><hr class="tbody-hr"/></td></tr></table></td></tr></table>

Comparison between the optimization methods.

Mathematical Problems in Engineering

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Table 4

Table 4: A Comparative Study of Fuzzy Logic, Genetic Algorithm, and Gradient-Genetic Algorithm Optimization Methods for Solving the Unit Commitment Problem 

Table 4 | A Comparative Study of Fuzzy Logic, Genetic Algorithm, and Gradient-Genetic Algorithm Optimization Methods for Solving the Unit Commitment Problem 