Bin packing and cutting stock problems: Mathematical models and exact algorithms
We review the most important mathematical models and algorithms developed for the exact
solution of the one-dimensional bin packing and cutting stock problems, and experimentally …
solution of the one-dimensional bin packing and cutting stock problems, and experimentally …
Approximation and online algorithms for multidimensional bin packing: A survey
The bin packing problem is a well-studied problem in combinatorial optimization. In the
classical bin packing problem, we are given a list of real numbers in (0, 1] and the goal is to …
classical bin packing problem, we are given a list of real numbers in (0, 1] and the goal is to …
Looking beyond {GPUs} for {DNN} scheduling on {Multi-Tenant} clusters
Training Deep Neural Networks (DNNs) is a popular workload in both enterprises and cloud
data centers. Existing schedulers for DNN training consider GPU as the dominant resource …
data centers. Existing schedulers for DNN training consider GPU as the dominant resource …
Allocation of virtual machines in cloud data centers—a survey of problem models and optimization algorithms
ZÁ Mann - Acm Computing Surveys (CSUR), 2015 - dl.acm.org
Data centers in public, private, and hybrid cloud settings make it possible to provision virtual
machines (VMs) with unprecedented flexibility. However, purchasing, operating, and …
machines (VMs) with unprecedented flexibility. However, purchasing, operating, and …
Circuit compilation methodologies for quantum approximate optimization algorithm
The quantum approximate optimization algorithm (QAOA) is a promising quantum-classical
hybrid algorithm to solve hard combinatorial optimization problems. The multi-qubit …
hybrid algorithm to solve hard combinatorial optimization problems. The multi-qubit …
APPM: adaptive parallel processing mechanism for service function chains
J Cai, Z Huang, L Liao, J Luo… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
By replacing traditional hardware-based middleboxes with software-based Virtual Network
Functions (VNFs) running on general-purpose servers, network function virtualization …
Functions (VNFs) running on general-purpose servers, network function virtualization …
Accelerating primal solution findings for mixed integer programs based on solution prediction
Abstract Mixed Integer Programming (MIP) is one of the most widely used modeling
techniques for combinatorial optimization problems. In many applications, a similar MIP …
techniques for combinatorial optimization problems. In many applications, a similar MIP …
Bin-packing
B Korte, J Vygen, B Korte, J Vygen - Kombinatorische Optimierung: Theorie …, 2012 - Springer
Angenommen, wir haben n Objekte verschiedener fester Größen und einige Behälter von
gleicher Größe. Unser Problem ist es, die Objekte den Behältern zuzuordnen, mit dem Ziel …
gleicher Größe. Unser Problem ist es, die Objekte den Behältern zuzuordnen, mit dem Ziel …
A simulated annealing approach for the circle bin packing problem with rectangular items
We introduce a new variant of Bin Packing Problem (BPP) called the Circular Bin Packing
Problem with Rectangular Items (CBPP-RI). CBPP-RI involves the dense orthogonal …
Problem with Rectangular Items (CBPP-RI). CBPP-RI involves the dense orthogonal …
Towards reliable robot packing system based on deep reinforcement learning
Object packing by a robot has a wide range of applications in the logistics industry. This task
requires the variable size items to be picked from piles one by one and then packed into …
requires the variable size items to be picked from piles one by one and then packed into …