On Rearrangement of Items Stored in Stacks.

There are $n \ge 2$ stacks, each filled with $d$ items (its full capacity), and one empty stack with capacity $d$. A robot arm, in one stack operation (move), may pop one item from the top of a non-empty stack and subsequently push it into a stack that is not at capacity. In a {\em labeled} problem, all $nd$ items are distinguishable and are initially randomly scattered in the $n$ stacks. The items must be rearranged using pop-and-push moves so that at the end, the $k^{\rm th}$ stack holds items $(k-1)d +1, \ldots, kd$, in that order, from the top to the bottom for all $1 \le k \le n$. In an {\em unlabeled} problem, the $nd$ items are of $n$ types of $d$ each. The goal is to rearrange items so that items of type $k$ are located in the $k^{\rm th}$ stack for all $1 \le k \le n$. In carrying out the rearrangement, a natural question is to find the least number of required pop-and-push moves. In terms of the required number of moves for solving the rearrangement problems, the labeled and unlabeled version have lower bounds $\Omega(nd + nd{\frac{\log d}{\log n}})$ and $\Omega(nd)$, respectively. Our main contribution is the design of an algorithm with a guaranteed upper bound of $O(nd)$ for both versions when $d \le cn$ for arbitrary fixed positive number $c$. In addition, a subroutine for a problem that we call the Rubik table problem is of independent interest, with applications to problems including multi-robot motion planning.