scholarly journals Distributed constraint satisfaction problems to model railway scheduling problems

2006 ◽  
Author(s):  
P. Tormos ◽  
M. Abril ◽  
M. A. Salido ◽  
F. Barber ◽  
L. Ingolotti ◽  
...  
Keyword(s):  
Constraint Satisfaction ◽  
Constraint Satisfaction Problems ◽  
Scheduling Problems ◽  
Distributed Constraint Satisfaction

scholarly journals Semantic Width and the Fixed-Parameter Tractability of Constraint Satisfaction Problems

2020 ◽  
Author(s):  
Hubie Chen ◽  
Georg Gottlob ◽  
Matthias Lanzinger ◽  
Reinhard Pichler
Keyword(s):  
Constraint Satisfaction ◽  
Fundamental Problem ◽  
Constraint Satisfaction Problems ◽  
Fixed Parameter Tractability ◽  
Scheduling Problems ◽  
Fixed Parameter Tractable ◽  
Database Theory ◽  
Formal Framework ◽  
Fixed Parameter

Constraint satisfaction problems (CSPs) are an important formal framework for the uniform treatment of various prominent AI tasks, e.g., coloring or scheduling problems. Solving CSPs is, in general, known to be NP-complete and fixed-parameter intractable when parameterized by their constraint scopes. We give a characterization of those classes of CSPs for which the problem becomes fixed-parameter tractable. Our characterization significantly increases the utility of the CSP framework by making it possible to decide the fixed-parameter tractability of problems via their CSP formulations. We further extend our characterization to the evaluation of unions of conjunctive queries, a fundamental problem in databases. Furthermore, we provide some new insight on the frontier of PTIME solvability of CSPs. In particular, we observe that bounded fractional hypertree width is more general than bounded hypertree width only for classes that exhibit a certain type of exponential growth. The presented work resolves a long-standing open problem and yields powerful new tools for complexity research in AI and database theory.

Multi-Layer Distributed Constraint Satisfaction for Multi-criteria Optimization Problem

2020 ◽  
Vol 11 (2) ◽  
pp. 134-155 ◽  
Author(s):  
Mouna Gargouri Mnif ◽  
Sadok Bouamama
Keyword(s):  
Constraint Satisfaction ◽  
Optimization Problem ◽  
Transportation Network ◽  
Optimization Methods ◽  
Planning Problem ◽  
Scheduling Problems ◽  
Present Contribution ◽  
Multimodal Transportation ◽  
New Approach ◽  
Distributed Constraint Satisfaction

This article introduces a new approach to solve the multimodal transportation network planning problem (MTNP). In this problem, the commodities must be transported from an international network by at least two different transport modes. The main purpose is to identify the best multimodal transportation strategy. The present contribution focuses on efficient optimization methods to solve MTNP. This includes the assignment and the scheduling problems. The authors split the MTNP into layered. Each layer is presented by an agent. These agents interact, collaborate, and communicate together to solve the problem. This article defines MTNP as a distributed constraint satisfaction multi-criteria optimization problem (DCSMOP). This latter is a description of the constraint optimization problem (COP), where variables and constraints are distributed among a set of agents. Each agent can interact with other agents to share constraints and to distribute complementary tasks. Experimental results are the proof of this work efficiently.

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