We investigate the computational hardness of the
type of Range Assignment Problems in ℝ
. We present new reductions for the Connectivity problem, which are easily adapted to suit the other two problems. All reductions are considerably simpler than the technically quite involved ones used in earlier works on these problems. Using our constructions, we can for the first time prove NP-hardness of these problems for
real distance-power gradients
> 0 (resp.
> 1 for
) in 2-d, and prove APX-hardness of all three problems in 3-d for
> 1. Our reductions yield improved lower bounds on the approximation ratios for all problems where APX-hardness was known before already. In particular, we derive the overall first APX-hardness proof for Broadcast. This was an open problem posed in earlier work in this area, as was the question whether (Strong) Connectivity remains NP-hard for
= 1. Additionally, we give the first hardness results for so-called well-spread instances.