scholarly journals Parallel Online Algorithms for the Bin Packing Problem

2020 ◽  
pp. 106-119
Author(s):  
Sándor P. Fekete ◽  
Jonas Grosse-Holz ◽  
Phillip Keldenich ◽  
Arne Schmidt
Keyword(s):  
Online Algorithms ◽  
Bin Packing ◽  
Packing Problem ◽  
Bin Packing Problem

An iteratively doubling local search for the two-dimensional irregular bin packing problem with limited rotations

2021 ◽  
pp. 105550
Author(s):  
Hao Zhang ◽  
Qiang Liu ◽  
Lijun Wei ◽  
Jiawei Zeng ◽  
Jiewu Leng ◽  
...  
Keyword(s):  
Local Search ◽  
Bin Packing ◽  
Packing Problem ◽  
Two Dimensional ◽  
Bin Packing Problem

An improved heuristic and an exact algorithm for the 2D strip and bin packing problem

2010 ◽  
Vol 10 (1/2/3) ◽  
pp. 217 ◽  
Author(s):  
Abdelghani Bekrar ◽  
Imed Kacem ◽  
Chengbin Chu ◽  
Cherif Sadfi
Keyword(s):  
Bin Packing ◽  
Exact Algorithm ◽  
Packing Problem ◽  
Bin Packing Problem

scholarly journals Heuristics Algorithms Based on a Linear Programming for the Three-Dimensional Bin-Packing Problem

2010 ◽  
Vol 43 (8) ◽  
pp. 72-76 ◽  
Author(s):  
Mhand Hifi ◽  
Imed Kacem ◽  
Stephane Negre ◽  
Lei Wu
Keyword(s):  
Linear Programming ◽  
Bin Packing ◽  
Three Dimensional ◽  
Packing Problem ◽  
Bin Packing Problem

EVALUATION OF TASK ALLOCATION IN MESH-BASED MULTICOMPUTERS USING GENETIC, NEURAL, AND TRADITIONAL ALGORITHMS

1994 ◽  
Vol 03 (01) ◽  
pp. 47-60
Author(s):  
R.A. McCONNELL ◽  
B.L. MENEZES
Keyword(s):  
Task Allocation ◽  
Bin Packing ◽  
Packing Problem ◽  
Allocation Problem ◽  
Hopfield Network ◽  
Processor Allocation ◽  
Classical Level ◽  
Bin Packing Problem ◽  
Residual Space ◽  
Computer Tasks

This article compares three techniques for allocating tasks in a mesh-based multi-computer. Tasks are expressed as rectangles of a certain width and height corresponding to the topology of processors desired. The task allocation problem, is thus a variant of the bin-packing problem, with one major difference: in the bin-packing problem one seeks to minimize the height of the bin, while here we seek to maximize the utilization of processors in a multicomputer. The three techniques compared are a classical level-by-level algorithm, a connectionist simulated annealing variant of the Hopfield network, and a genetic algorithm. An extension to the dynamic processor allocation problem is modeled by fixing some rectangles in place and packing the request rectangles in the residual space on the mesh; this corresponds to a pre-existing condition, i.e., some tasks have already been allocated to the Processor Mesh. Implementation and experimental results are presented.

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