Improved approximation algorithms for maximum resource bin packing and lazy bin covering problems

In this paper, we study two variants of the bin packing and covering problems called Maximum Resource Bin Packing (MRBP) and Lazy Bin Covering (LBC) problems, and present new approximation algorithms for them. For the offline MRBP problem, the previous best known approximation ratio is 6/5 (=1.2) achieved by the classical First-Fit-Increasing (FFI) algorithm (Boyar et al. in Theor. Comput. Sci. 362(1-3):127-139, 2006). In this paper, we give a new FFI-type algorithm with an approximation ratio of 80/71 (≈1.12676). For the offline LBC problem, it has been shown in Lin et al. (COCOON, pp. 340-349, 2006) that the classical First-Fit-Decreasing (FFD) algorithm achieves an approximation ratio of 71/60 (≈1.18333). In this paper, we present a new FFD-type algorithm with an approximation ratio of 17/15 (≈1.13333). Our algorithms are based on a pattern-based technique and a number of other observations. They run in near linear time (i.e., O(nlog n)), and therefore are practical.