JOURNAL ARTICLE

Decomposing Constraint Satisfaction Problems by Means of Meta Constraint Satisfaction Optimization Problems

Abstract

This paper describes a new approach to decompose constraint satisfaction problems (CSPs) using an auxiliary constraint satisfaction optimization problem (CSOP) that detects sub-CSPs which share only few common variables. The purpose of this approach is to find sub-CSPs which can be solved in parallel and combined to a complete solution of the original CSP. Therefore, our decomposition approach has two goals: 1. to evenly balance the workload distribution over all cores and solve the partial CSPs as fast as possible and 2. to minimize the number of shared variables to make the join process of the solutions as fast as possible.

Keywords:
Constraint satisfaction problem Constraint satisfaction dual problem Constraint satisfaction Local consistency Decomposition method (queueing theory) Computer science Constraint (computer-aided design) Mathematical optimization Constraint graph Backtracking Constraint logic programming Workload Decomposition Complexity of constraint satisfaction Constraint programming Hybrid algorithm (constraint satisfaction) Mathematics Algorithm Artificial intelligence Discrete mathematics

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Topics

Constraint Satisfaction and Optimization
Physical Sciences →  Computer Science →  Computer Networks and Communications
Scheduling and Optimization Algorithms
Physical Sciences →  Engineering →  Industrial and Manufacturing Engineering
Scheduling and Timetabling Solutions
Social Sciences →  Decision Sciences →  Management Science and Operations Research

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