JOURNAL ARTICLE

On Solving Boolean Multilevel Optimization Problems

Josep ArgelichInês LynceJoão Marques‐Silva

Year: 2009 Journal:   arXiv (Cornell University) Pages: 393-398   Publisher: Cornell University

Abstract

Many combinatorial optimization problems entail a number of hierarchically dependent optimization problems. An often used solution is to associate a suitably large cost with each individual optimization problem, such that the solution of the resulting aggregated optimization problem solves the original set of hierarchically dependent optimization problems. This paper starts by studying the package upgradeability problem in software distributions. Straightforward solutions based on Maximum Satisfiability (MaxSAT) and pseudo-Boolean (PB) optimization are shown to be ineffective, and unlikely to scale for large problem instances. Afterwards, the package upgradeability problem is related to multilevel optimization. The paper then develops new algorithms for Boolean Multilevel Optimization (BMO) and highlights a large number of potential applications. The experimental results indicate that the proposed algorithms for BMO allow solving optimization problems that existing MaxSAT and PB solvers would otherwise be unable to solve.

Keywords:
Maximum satisfiability problem Optimization problem Mathematical optimization Computer science Boolean satisfiability problem Set (abstract data type) Combinatorial optimization Satisfiability Theoretical computer science Algorithm Mathematics Boolean function

Metrics

25
Cited By
0.00
FWCI (Field Weighted Citation Impact)
22
Refs
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Constraint Satisfaction and Optimization
Physical Sciences →  Computer Science →  Computer Networks and Communications
Advanced Software Engineering Methodologies
Physical Sciences →  Computer Science →  Artificial Intelligence
Formal Methods in Verification
Physical Sciences →  Computer Science →  Computational Theory and Mathematics

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