The current mechanism utilized by Bitcoin Core is known as the ancestor-feerate transaction selection method, which has been in use for several years. There's a proposal for a cluster mempool strategy that promises to be more efficient by potentially offering a more optimal selection of transactions. This new algorithm is anticipated to outperform the legacy system when working under similar conditions, specifically with the same set of mempool transactions.

The quest for optimization also encounters inherent difficulties, especially when dealing with large transaction clusters. The ideal sorting of these clusters is believed to demand exponential time, a notion supported by the complexity of finding the highest value-weight ratio in a dependency graph being an NP-hard problem, as discussed on cs.stackexchange.com. Due to this, the approach being developed will likely resort to simpler, polynomial-time strategies, such as the aforementioned ancestor-feerate algorithm, for handling bigger clusters. This compromise, while necessary, may lead to results that fall short of being truly optimal.

Furthermore, the analysis addresses the knapsack problem, highlighting another layer of complexity in achieving optimal block composition. Even with a theoretically perfect sorting methodology based on the feerate diagram metric, there still exists the possibility of not having enough space at the end of a block for the next high-priority transaction chunk. A practical approach to estimating how close the system gets to the optimal solution involves examining how full a block is when it encounters a chunk that exceeds its remaining capacity. Although there’s an acknowledgment that, theoretically, the system might only guarantee about 90% optimality due to limitations in ancestor package sizes (capped at 101kvb), the actual efficiency is likely higher because most transactions are relatively small.

Overall, the exploration into optimizing block mining processes in Bitcoin highlights the balance between theoretical ideals and practical constraints. The introduction of a cluster mempool strategy presents a promising avenue for improvements over the traditional system, despite the challenges in achieving absolute optimality. Further research and development are expected to shed more light on these aspects, though detailed insights might take several months to materialize.