A Hybrid Technique Based on a Genetic Algorithm for Fuzzy Multiobjective Problems in 5G, Internet of Things, and Mobile Edge Computing

Algorithm 4

Mutation operator

(1)	Generate the random vector . Each component of the vector corresponds to one of the components of the solution vector.
(2)	For , if , assign a random value in to .
(3)	Check whether the solution is feasible. If it is not feasible, we modify the solution using Algorithm 3. This operator will give a variation to the value of the solution vector and prevent converging the population to the maximum solution. In this method, we consider the arbitrary parameter . This means each component of the solution has a 10 percent chance to be modified.