  In this paper, to address backhaul capacity bottleneck and concurrently
optimize energy consumption and delay, we formulate a novel weighted-sum
multi-objective optimization problem where popular content caching placement
and integrated access and backhaul (IAB) millimeter (mmWave) bandwidth
partitioning are optimized jointly to provide Pareto efficient optimal
non-dominating solutions. In such integrated networks analysis of what-if
scenarios to understand trade-offs in decision space, without losing sight of
optimality, is important. A wide set of numerical investigations reveal that
compared with the nominal single objective optimization schemes such as
optimizing only the delay or the energy consumption the proposed optimization
framework allows for a reduction of the aggregation of energy consumption and
delay by an average of 30% to 55%.
