Sparsity of integer formulations for binary programs

2019 ◽  
Vol 47 (5) ◽  
pp. 348-352
Author(s):  
Christopher Hojny ◽  
Hendrik Lüthen ◽  
Marc E. Pfetsch
Keyword(s):  
Integer Formulations ◽  
Binary Programs

Concise RLT forms of binary programs: A computational study of the quadratic knapsack problem

2009 ◽  
Vol 57 (1) ◽  
pp. 1-12 ◽  
Author(s):  
Richard J. Forrester ◽  
Warren P. Adams ◽  
Paul T. Hadavas
Keyword(s):  
Knapsack Problem ◽  
Computational Study ◽  
Quadratic Knapsack Problem ◽  
Quadratic Knapsack ◽  
Binary Programs

scholarly journals Disjunctive Decomposition for Two-Stage Stochastic Mixed-Binary Programs with Random Recourse

2010 ◽  
Vol 58 (1) ◽  
pp. 229-243 ◽  
Author(s):  
Lewis Ntaimo
Keyword(s):  
Two Stage ◽  
Binary Programs

SHFuzz: A hybrid fuzzing method assisted by static analysis for binary programs

2021 ◽  
Vol 18 (8) ◽  
pp. 1-16
Author(s):  
Wenjie Wang ◽  
Donghai Tian ◽  
Rui Ma ◽  
Hang Wei ◽  
Qianjin Ying ◽  
...  
Keyword(s):  
Static Analysis ◽  
Binary Programs

VulLocator: Automatically Locating Vulnerable Code in Binary Programs

2013 ◽  
pp. 295-308
Author(s):  
Yingjun Zhang ◽  
Kai Chen ◽  
Yifeng Lian
Keyword(s):  
Binary Programs

Modifying Transactional Databases to Hide Sensitive Association Rules

2021 ◽  
Author(s):  
Syam Menon ◽  
Abhijeet Ghoshal ◽  
Sumit Sarkar
Keyword(s):  
Supply Chain ◽  
Association Rules ◽  
Association Rule ◽  
Sensitive Information ◽  
Data Set ◽  
Problem Reduction ◽  
Transactional Databases ◽  
Potential Risks ◽  
Integer Formulations ◽  
Number Of Firms

Although firms recognize the value in sharing data with supply chain partners, many remain reluctant to share for fear of sensitive information potentially making its way to competitors. Approaches that can help hide sensitive information could alleviate such concerns and increase the number of firms that are willing to share. Sensitive information in transactional databases often manifests itself in the form of association rules. The sensitive association rules can be concealed by altering transactions so that they remain hidden when the data are mined by the partner. The problem of hiding these rules in the data are computationally difficult (NP-hard), and extant approaches are all heuristic in nature. To our knowledge, this is the first paper that introduces the problem as a nonlinear integer formulation to hide the sensitive association rule while minimizing the alterations needed in the data set. We apply transformations that linearize the constraints and derive various results that help reduce the size of the problem to be solved. Our results show that although the nonlinear integer formulations are not practical, the linearizations and problem-reduction steps make a significant impact on solvability and solution time. This approach mitigates potential risks associated with sharing and should increase data sharing among supply chain partners.

Mixed integer formulations for a coupled lot-scheduling and vehicle routing problem in furniture settings

2019 ◽  
Vol 57 (4) ◽  
pp. 563-596 ◽  
Author(s):  
Pedro L. Miranda ◽  
Reinaldo Morabito ◽  
Deisemara Ferreira
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Mixed Integer ◽  
Routing Problem ◽  
Lot Scheduling ◽  
Integer Formulations

A simple, all primal branch and bound approach to pure and mixed integer binary programs

1982 ◽  
Vol 1 (5) ◽  
pp. 182-185 ◽  
Author(s):  
Gary A. Kochenberger ◽  
Victor H. Richard
Keyword(s):  
Branch And Bound ◽  
Mixed Integer ◽  
Binary Programs
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