We analyze the problem of packing squares in an online fashion: Given a semi-infinite strip of width 1 and an unknown sequence of squares of side length in [0,1] that arrive from above, one at a time. The objective is to pack these items as they arrive, minimizing the resulting height. Just like in the classical game of Tetris, each square must be moved along a collision-free path to its final destination. In addition, we account for gravity in both motion (squares must never move up) and position (any final destination must be supported from below). A similar problem has been considered before; the best previous result is by Azar and Epstein, who gave a 4-competitive algorithm in a setting without gravity (i.e., with the possibility of letting squares "hang in the air") based on ideas of shelf-packing: Squares are assigned to different horizontal levels, allowing an analysis that is reminiscent of some bin-packing arguments. We apply a geometric analysis to establish a competitive factor of 3.5 for the bottom-left heuristic and present a 34 13=2.615...-competitive algorithm.
strip packing problem!Tetris and gravity constraint There is one negative result for the setting with Tetris and gravity constraint when rotation is not allowed in @cite_12 : If all rectangles have a width of at least @math or of at most @math , then the competitive factor of any algorithms is @math .
@cite_12
2098666887 2012437618 1586863324 2060963575
We study strip packing, which is one of the most classical two-dimensional packing problems: given a collection of rectangles, the problem is to find a feasible orthogonal packing without rotations into a strip of width 1 and minimum height. In this paper we present an approximation algorithm for the strip packing problem with absolute approximation ratio of 5 3+@e for any @e>0. This result significantly narrows the gap between the best known upper bound and the lower bound of 3 2; previously, the best upper bound was 1.9396 due to Harren and van Stee. Rectangles with dimensions independently chosen from a uniform distribution on [0, 1] are packed on-line into a unit width strip under a constraint like that of the Tetris game: rectangles arrive from the top and must be moved inside the strip to reach their place; once placed, they cannot be moved again. Cargo loading applications impose similar constraints. This paper assumes that rectangles must be moved without rotation. For n rectangles, the resulting packing height is shown to have an asymptotic expected value of at least (0.31382733 ... )n under any on-line packing algorithm. An on-line algorithm is presented that achieves an asymptotic expected height of (0.36976421 ... )n. This algorithm improves the bound achieved in Next Fit Level (NFL) packing, by compressing the items packed on two successive levels of an NFL packing via on-line movement admissible under the Tetris-like constraint. We consider the two-dimensional bin packing and strip packing problem, where a list of rectangles has to be packed into a minimal number of rectangular bins or a strip of minimal height, respectively. All packings have to be non-overlapping and orthogonal, i.e., axis-parallel. Our algorithm for strip packing has an absolute approximation ratio of 1.9396 and is the first algorithm to break the approximation ratio of 2 which was established more than a decade ago. Moreover, we present a polynomial time approximation scheme ( @math ) for strip packing where rotations by 90 degrees are permitted and an algorithm for two-dimensional bin packing with an absolute worst-case ratio of 2, which is optimal provided @math . We present an asymptotic fully polynomial approximation scheme for strip-packing, or packing rectangles into a rectangle of fixed width and minimum height, a classicalNP-hard cutting-stock problem. The algorithm, based on a new linear-programming relaxation, finds a packing ofn rectangles whose total height is within a factor of (1 +e) of optimal (up to an additive term), and has running time polynomial both in n and in 1 e.