Title :
How to pack better than best fit: tight bounds for average-case online bin packing
Author_Institution :
AT&T Bell Lab., Murray Hill, NJ, USA
Abstract :
An O(n log n)-time online algorithm is given for packing items i.i.d. uniform on [0, 1] into bins of size 1 with expected wasted space Θ(n1/2 log 1/2 n). This matches the lowest bound that no online algorithm can achieve O(n1/2 log 1/2 n) wasted space. It is done by analyzing another algorithm which involves putting balls into buckets online. The analysis of this second algorithm also gives bound on the stochastic rightward matching problem, which arises in analyzing not only the above online bin packing problem, but also a 2-D problem of packing rectangles into a half-infinite strip. The bounds on rightward matching thus give good bounds for the 2-D strip packing problem
Keywords :
computational complexity; operations research; 2-D strip packing problem; average-case online bin packing; ball packing; expected wasted space; half-infinite strip; lowest bound; online algorithm; rectangle packing; stochastic rightward matching problem; tight bounds; Algorithm design and analysis; Harmonic analysis; NP-complete problem; Optimized production technology; Performance analysis; Polynomials; Strips; Testing;
Conference_Titel :
Foundations of Computer Science, 1991. Proceedings., 32nd Annual Symposium on
Conference_Location :
San Juan
Print_ISBN :
0-8186-2445-0
DOI :
10.1109/SFCS.1991.185444