Interference-aware spectrum planning for heterogeneous satellite, aerial, maritime, and terrestrial platforms requires discrete frequency decisions under conflicting reuse, adjacent-channel leakage, and service-protection objectives. This paper develops reference-direction promising-list discrete multi-objective particle swarm optimization (RDPL-MOPSO) coupled to an allocation-induced physical interference audit. Candidate-frequency indices are treated as categories rather than ordinal coordinates. Fixed reference directions align particle leaders, personal-best replacement, and archive niches, while a strict promising-list search enumerates candidate bands for audit-ranked high-risk payloads. The physical evaluation combines free-space path loss, transmitter leakage, receiver selectivity, adjacent-channel interference-ratio attenuation, receiver protection thresholds, public occupancy calibration, and final all-pair re-scoring. Configuration selection is restricted to controlled synthetic training and validation instances before evaluation on frozen Southern California public-observation-calibrated benchmarks with 100 and 200 payloads and 20 matched seeds. RDPL-MOPSO achieves the highest mean hypervolume and lowest mean inverted generational distance among all tested solvers at both scales, with Holm-corrected paired comparisons supporting its advantage over same-audit-feedback NSGA-II and SPEA2 controls. Independent receiver-side diagnostics aggregate all co-channel and in-window adjacent-channel interference under matched 0--6 dB log-normal shadowing; RDPL-MOPSO retains the best mean demand preservation and receiver-protection rate, although not every diagnostic difference is statistically significant. The results establish empirical superiority under the frozen protocol, not mathematical global optimality or field-trial validation.

Dynamic spectrum reallocation must mitigate severe link degradation under limited search and frequency switching. We study a risk-triggered controller combining receiver/aggressor ranking, screened greedy repair and conditional two-coordinate refinement under cumulative co-channel and adjacent channel interference. With four frequency candidates per link and a 12-link greedy screen, each noninitial decision requires at most 104 physical evaluations and respects a hard switching limit. Component, disturbance recovery and single-factor experiments characterize the operating trade-offs. Findings from these studies motivate a separately frozen tail risk validation using 30 new seeds at each of two network sizes, yielding 240 closed-loop trajectories. Its sole primary endpoint is the trajectory-mean cross-link conditional value-at-risk of signal-to-interference-plus-noise ratio (SINR) shortfall. In the prescribed 30-link scenarios, the controller reduces this endpoint by 10.61% against ranked coordinate search and 11.97% against a literature-informed memetic reference. Both comparisons survive Holm correction. An advantage over the no-refinement ablation is not established, nor is any primary comparison at 14 links. All methods fail to attain fully feasible slots in the 30-link validation. A separate screening size sensitivity study finds lower 30-link tail risk with a 24-link screen under the same evaluation ceiling; the original 12-link choice is therefore not optimal among the tested settings. Post-review rescorings of the R4 decisions retain the 30-link comparator advantages for raw dB shortfall but not the absolute linear SINR shortfall. Thus, the observed ranking depends on the declared loss definition. The evidence therefore supports conditional mitigation of severe link degradation under that definition, not metric-independent superiority, service-level compliance or an end-to-end real-time guarantee.