Recent research in combinatorial bin-packing models is extended to a stochastic model in which an arbitrary distribution of piece sizes is assumed. The asymptotic expected bin occupancy is obtained for a simple on-line algorithm. Convergence properties are also presented so that, for a given set of pieces, this measure can be related to the expected number of bins required relative to an optimization rule
This thesis focuses on algorithms solving the on-line Bin-Covering problem, when the items are gene...
We introduce and study the batched bin packing problem (BBPP), a bin packing problem in which items ...
Abstract. In the bin packing problem we are given an instance consist-ing of a sequence of items wit...
Recent research in combinatorial bin-packing models is extended to a stochastic model in which an ar...
AbstractThe Generalized Bin Packing Problem (GBPP) is a recently introduced packing problem where, g...
We study the online bin packing problem under two stochastic settings. In the bin packing problem, w...
In the dual bin packing problem, the objective is to assign items of given size to the largest possi...
(eng) We study of the average case performance of the Best Fit algorithm for on-line bin packing und...
We analyze the one-dimensional bin-packing problem under the assumption that bins have unit capacity...
In the past few years, there has been a strong and growing interest in evaluating the expected behav...
In this paper, we extend the classical Variable Size Bin Packing Problem (VS-BPP) by adding time fea...
Items of various types arrive at a bin-packing facility according to random processes and are to be ...
Abstract. We consider the one-dimensional bin packing problem with unit-capacity bins and item sizes...
AbstractThis paper investigates a new version of the on-line variable-sized bin packing problem. Sup...
AbstractWe consider a natural resource allocation problem in which we are given a set of items, wher...
This thesis focuses on algorithms solving the on-line Bin-Covering problem, when the items are gene...
We introduce and study the batched bin packing problem (BBPP), a bin packing problem in which items ...
Abstract. In the bin packing problem we are given an instance consist-ing of a sequence of items wit...
Recent research in combinatorial bin-packing models is extended to a stochastic model in which an ar...
AbstractThe Generalized Bin Packing Problem (GBPP) is a recently introduced packing problem where, g...
We study the online bin packing problem under two stochastic settings. In the bin packing problem, w...
In the dual bin packing problem, the objective is to assign items of given size to the largest possi...
(eng) We study of the average case performance of the Best Fit algorithm for on-line bin packing und...
We analyze the one-dimensional bin-packing problem under the assumption that bins have unit capacity...
In the past few years, there has been a strong and growing interest in evaluating the expected behav...
In this paper, we extend the classical Variable Size Bin Packing Problem (VS-BPP) by adding time fea...
Items of various types arrive at a bin-packing facility according to random processes and are to be ...
Abstract. We consider the one-dimensional bin packing problem with unit-capacity bins and item sizes...
AbstractThis paper investigates a new version of the on-line variable-sized bin packing problem. Sup...
AbstractWe consider a natural resource allocation problem in which we are given a set of items, wher...
This thesis focuses on algorithms solving the on-line Bin-Covering problem, when the items are gene...
We introduce and study the batched bin packing problem (BBPP), a bin packing problem in which items ...
Abstract. In the bin packing problem we are given an instance consist-ing of a sequence of items wit...
DOI
Add to ORKG