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

Algorithm 2

The proposed algorithm for fuzzy multiobjective problems.

	Suppose is the number of individuals generated, is the size of the efficient set, is the maximum of the generation.
(1)	Set .
(2)	Generate the primary set using Algorithm 1.
(3)	Use the selection and reproduction method. Choose the effective solutions from the primary set and put them in .
(4)	Use the mutation operator.
(5)	Use the crossover operator.
(6)	Use the selection and reproduction method and update the set . After generating, if , use the fuzzy clustering to reduce the size of the efficient set.
(7)	If , set and go to step 4.
(8)	Use the local improvement for the set . In establishing this algorithm, we normally set