  The problem of merging sorted lists in the least number of pairwise
comparisons has been solved completely only for a few special cases. Graham and
Karp \cite{taocp} independently discovered that the tape merge algorithm is
optimal in the worst case when the two lists have the same size. In the seminal
papers, Stockmeyer and Yao\cite{yao}, Murphy and Paull\cite{3k3}, and
Christen\cite{christen1978optimality} independently showed when the lists to be
merged are of size $m$ and $n$ satisfying $m\leq
n\leq\lfloor\frac{3}{2}m\rfloor+1$, the tape merge algorithm is optimal in the
worst case. This paper extends this result by showing that the tape merge
algorithm is optimal in the worst case whenever the size of one list is no
larger than 1.52 times the size of the other. The main tool we used to prove
lower bounds is Knuth's adversary methods \cite{taocp}. In addition, we show
that the lower bound cannot be improved to 1.8 via Knuth's adversary methods.
We also develop a new inequality about Knuth's adversary methods, which might
be interesting in its own right. Moreover, we design a simple procedure to
achieve constant improvement of the upper bounds for $2m-2\leq n\leq 3m $.
