While this paper focuses on optimizing sensor placement for methane emission detection efficiency, the algorithm can be extended to various other applications, involving emission localization and quantification, by simply changing the objective function in the optimization problem. This flexibility is due to the genetic algorithm's ability to handle non-linear objective functions, a capability not possible with the Mixed-Integer Linear Programming (MILP) approach adopted in prior studies.