Today I see this as an exercise where a scholar would implement each one while collecting metrics to feed the report on which did better at your target goals.
No one here can guess your application but once in a while a new grad study will think there is an off the shelf answer. I remember this sort of study from over a decade ago and today my view has changed to "build it, measure and report."
I studied 4 algorithms and my advisor asked which one is best for optimizing hetnet handover taking into consideration optimizing both sumrate and energy expenditure, the algorithms are:
Multi-Objective Genetic Algorithm
Non-dominated Sorting Genetic Algorithm
Strength Pareto Evolutionary Algorithm
e-dominance Multi-Objective Evolutionary Algorithm
which would you say is the best for the best choice so as to balance rate distribution and lower energy expenditure???