Parallel Branch-and-Bound Algorithms for General Mixed Integer Programming on the CM-5

1994 ◽  
Vol 4 (4) ◽  
pp. 794-814 ◽  
Author(s):  
Jonathan Eckstein
Keyword(s):  
Integer Programming ◽  
Mixed Integer Programming ◽  
Branch And Bound ◽  
Mixed Integer ◽  
Branch And Bound Algorithms ◽  
Parallel Branch And Bound

scholarly journals A hybrid branch-and-bound approach for exact rational mixed-integer programming

2013 ◽  
Vol 5 (3) ◽  
pp. 305-344 ◽  
Author(s):  
William Cook ◽  
Thorsten Koch ◽  
Daniel E. Steffy ◽  
Kati Wolter
Keyword(s):  
Integer Programming ◽  
Mixed Integer Programming ◽  
Branch And Bound ◽  
Mixed Integer

scholarly journals Estimating the size of search trees by sampling with domain knowledge

2017 ◽  
Author(s):  
Gleb Belov ◽  
Samuel Esler ◽  
Dylan Fernando ◽  
Pierre Le Bodic ◽  
George L. Nemhauser
Keyword(s):  
Integer Programming ◽  
Mixed Integer Programming ◽  
Branch And Bound ◽  
Domain Knowledge ◽  
Estimation Error ◽  
Search Tree ◽  
Branch And Bound Algorithm ◽  
Mixed Integer ◽  
Search Trees ◽  
Sampling Algorithm

We show how recently-defined abstract models of the Branch-and-Bound algorithm can be used to obtain information on how the nodes are distributed in B&B search trees. This can be directly exploited in the form of probabilities in a sampling algorithm given by Knuth that estimates the size of a search tree. This method reduces the offline estimation error by a factor of two on search trees from Mixed-Integer Programming instances.

Optimal Distributed Generator Allocation in Active Distribution Network Considering Reconfiguration

2014 ◽  
Vol 672-674 ◽  
pp. 1117-1122
Author(s):  
Yu De Yang ◽  
Hong Bo Xie
Keyword(s):  
Integer Programming ◽  
Mixed Integer Programming ◽  
Branch And Bound ◽  
Distribution Network ◽  
Mixed Integer ◽  
Branch And Bound Method ◽  
Allocation Model ◽  
Distributed Generator ◽  
Active Distribution Network ◽  
Planning And Operation

For the structure of active distribution network can flexibly adjust, an optimal distributed generator allocation model considering reconfiguration is proposed. This model is implemented in the GAMS software and solved using SBB solver based on branch and bound method, due to it is a 0-1 nonlinear mixed integer programming. IEEE 33 standard example is used to simulate for this model. Results show that reconfiguration can increase the capacity of absorbing DG, providing thoughts and guidance for confirming the capacity of DG, and for planning and operation of active distribution network.

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