In early seventies it was shown that the asymptotic approximation ratio of BestFit bin packing is equal to 1.7. We prove that also the absolute approximation ratio for BestFit bin packing is exactly 1.7, improving the previous bound of 1.75. This means that if the optimum needs Opt bins, BestFit always uses at most b1.7 · OPTc bins. Fur-thermore we show matching lower bounds for all values of Opt, i.e., we give instances on which BestFit uses exactly b1.7 · OPTc bins. Thus we completely settle the worst-case complexity of BestFit bin packing after more than 40 years of its study
In this paper we consider the familiar bin-packing problem and its associated set-partitioning formu...
This paper examines the monotonicity of the approximation bin packing algorithms Worst-Fit (WF), Wor...
We analyze the worst-case ratio of natural variations of the so-called subset sum heuristic for the ...
We give a simple proof and a generalization of the classical result which says that the (asymptotic)...
In the bin packing problem we are given an instance consisting of a sequence of items with sizes bet...
Abstract. In the bin packing problem we are given an instance consist-ing of a sequence of items wit...
AbstractWe revisit three famous bin packing algorithms, namely Next Fit (NF), Worst Fit (WF) and Fir...
AbstractIt is well known that the two simple algorithms for the classic bin packing problem, NF and ...
AbstractIn this paper, we present improved bounds for the First Fit algorithm for the bin-packing pr...
We analyze the worst-case ratio of a natural heuristic for the bin packing problem, which proceeds b...
Best-fit is the best known algorithm for on-line bin-packing, in the sense that no algorithm is know...
AbstractUsually, for bin packing problems, we try to minimize the number of bins used or in the case...
AbstractThe FIRST FIT DECREASING algorithm for bin packing has long been famous for its guarantee th...
Abstract. We analyze the approximation behavior of some of the best-known polynomial-time approximat...
Due to the character of the original source materials and the nature of batch digitization, quality ...
In this paper we consider the familiar bin-packing problem and its associated set-partitioning formu...
This paper examines the monotonicity of the approximation bin packing algorithms Worst-Fit (WF), Wor...
We analyze the worst-case ratio of natural variations of the so-called subset sum heuristic for the ...
We give a simple proof and a generalization of the classical result which says that the (asymptotic)...
In the bin packing problem we are given an instance consisting of a sequence of items with sizes bet...
Abstract. In the bin packing problem we are given an instance consist-ing of a sequence of items wit...
AbstractWe revisit three famous bin packing algorithms, namely Next Fit (NF), Worst Fit (WF) and Fir...
AbstractIt is well known that the two simple algorithms for the classic bin packing problem, NF and ...
AbstractIn this paper, we present improved bounds for the First Fit algorithm for the bin-packing pr...
We analyze the worst-case ratio of a natural heuristic for the bin packing problem, which proceeds b...
Best-fit is the best known algorithm for on-line bin-packing, in the sense that no algorithm is know...
AbstractUsually, for bin packing problems, we try to minimize the number of bins used or in the case...
AbstractThe FIRST FIT DECREASING algorithm for bin packing has long been famous for its guarantee th...
Abstract. We analyze the approximation behavior of some of the best-known polynomial-time approximat...
Due to the character of the original source materials and the nature of batch digitization, quality ...
In this paper we consider the familiar bin-packing problem and its associated set-partitioning formu...
This paper examines the monotonicity of the approximation bin packing algorithms Worst-Fit (WF), Wor...
We analyze the worst-case ratio of natural variations of the so-called subset sum heuristic for the ...