Priority queues are essential function blocks in numerous applications such as discrete event simulations. This paper describes and exemplifies the ease of obtaining high performance priority queues using a two-tier list-based structure. This new implementation, called the Twol structure, is amalgamated with three priority queues, namely, the Henriksen's queue, splay tree and skew heap, to enhance the efficiency of these basal priority queue structures. Using a model that combines traditional average case and amortized complexity analysis, Twol-amalgamated priority queues that maintain N active events are theoretically proven to offer O(1) expected amortized complexity under reasonable assumptions. They are also demonstrated empirically to offer stable near O(1) performance for widely varying priority increment distributions and for queue sizes ranging from 10 to 10 million. Extensive empirical results show that the Twol-amalgamated priority queues consistently outperform those basal structures (i.e., without the Twol structure) with an average speedup of about three to five times on widely different hardware architectures. These results provide testimony that the Twol-amalgamated priority queues are suitable for implementation in sizeable application scenarios such as, but not limited to, large-scale discrete event simulation.