Distributed CSPs by graph partitioning

Engineering Applications of Artificial Intelligence

Giret

2008

Self Cite

Nowadays, many real problems can be formalized as Distributed CSPs. A distributed constraint satisfaction problem (DisCSP) is a CSP in which variables and constraints are distributed among multiple automated agents. Many researchers assume for simplicity that each agent has exactly one variable. For real planning and scheduling problems, these distributed techniques require a large amount of messages passed among agents, so these problems are very difficult to solve. In this paper, we present a general distributed model for solving real-life scheduling problems and propose some guidelines for distributing large-scale problems. Furthermore, we present two case studies in which two scheduling problems are distributed by using our model.

Section: Some Guidelines For Distributing Large-scale Problemsmentioning

confidence: 99%

“…(Salido 2007). Only some works include a set of variables into an agent (Silaghi & Faltings 2005), (Ezzahir & Bouyakhf 2007), (Salido & Barber 2006). Nevertheless, few works have been focused on distributed techniques for solving large scale problems (Yokoo et al 1998).…”

Section: From Basic Research Toward Applied Researchmentioning

confidence: 99%

Feasible distributed CSP models for scheduling problems

Engineering Applications of Artificial Intelligence

Giret

2008

Self Cite

“…Only some works include a set of variables into an agent (Salido & Barber, 2006), (Ezzahir et al, 2007). Therefore, more research must be done to solve more realistic problems.…”

Section: Distributed Agentsmentioning

confidence: 99%

New trends in constraint satisfaction, planning, and scheduling: a survey

Barták

The Knowledge Engineering Review

Rossi

2010

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During recent years the development of new techniques for constraint satisfaction, planning, and scheduling has received increased attention, and substantial effort has been invested in trying to exploit such techniques to find solutions to real life problems. In this paper, we present a survey on constraint satisfaction, planning and scheduling from the Artificial Intelligence point of view. In particular, we present the main definitions and techniques, and we discuss possible ways of integrating such techniques. We also analyze the role of constraint satisfaction in planning and scheduling, and we hint at some open research issues related to planning, scheduling and constraint satisfaction.

“…Thus, we can use graph partitioning when dealing with large-scale CSPs to distribute the problem into a set of sub-CSPs. For instance, we can divide a CSP into several subCSPs so that constraints among variables of each sub-CSP are minimized (Salido & Barber 2006).…”

Section: Preprint Submitted To Elseviermentioning

confidence: 99%

Distributed search in railway scheduling problems

Abril

Engineering Applications of Artificial Intelligence

Barber

2008

Self Cite

Many problems of theoretical and practical interest can be formulated as Constraint Satisfaction Problems (CSPs). Solving a general CSP is known to be NP-complete; however, distributed models may take advantage of dividing the problem into a set of simpler interconnected sub-problems which can be more easily solved. The purpose of this paper is threefold: first, we present a technique to distribute the constraint network by means of selection of tree structures. Thus, the CSP is represented as a meta-tree CSP structure that is used as a hierarchy of communication by our distributed algorithm. Then, a distributed and asynchronous search algorithm (DTS) is presented. DTS is committed to solving the meta-tree CSP structure in a Depth-First Search Tree. Finally, an intra-agent search algorithm is presented. This algorithm takes into account the Nogood message to prune the search space. We have focused our research on the railway scheduling problem which can be distributed by tree structures. We show that our distributed algorithm outperforms well-known centralized algorithms.