TY - CHAP

T1 - Scheduling agents - Distributed Timetabling Problems

AU - Meisels, Amnon

AU - Kaplansky, Eliezer

PY - 2003

Y1 - 2003

N2 - Many real-world Timetabling Problems are composed of organizational parts that need to timetable their staff in an independent way, while adhering to some global constraints. Later, the departmental timetables are combined to yield a coherent, consistent solution. This last phase involves negotiations with the various agents and requests for changes in their own solutions. Most of the real-world distributed timetabling problems that fall into this class have global constraints that involve many of the agents in the system. Models that use networks of binary constraints are inadequate. As a result, this paper proposes a new model that contains only one additional agent: the Central Agent that coordinates the search process of all Scheduling Agents (SAs). Preliminary experiments show that a sophisticated heuristic is needed for the CA to effectively interact with its scheduling agents in order to find an optimal solution. The approach and the results reported in this paper are an initial attempt to investigate possible solution methods for networks of SAs.

AB - Many real-world Timetabling Problems are composed of organizational parts that need to timetable their staff in an independent way, while adhering to some global constraints. Later, the departmental timetables are combined to yield a coherent, consistent solution. This last phase involves negotiations with the various agents and requests for changes in their own solutions. Most of the real-world distributed timetabling problems that fall into this class have global constraints that involve many of the agents in the system. Models that use networks of binary constraints are inadequate. As a result, this paper proposes a new model that contains only one additional agent: the Central Agent that coordinates the search process of all Scheduling Agents (SAs). Preliminary experiments show that a sophisticated heuristic is needed for the CA to effectively interact with its scheduling agents in order to find an optimal solution. The approach and the results reported in this paper are an initial attempt to investigate possible solution methods for networks of SAs.

UR - http://www.scopus.com/inward/record.url?scp=35248843253&partnerID=8YFLogxK

U2 - 10.1007/978-3-540-45157-0_11

DO - 10.1007/978-3-540-45157-0_11

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AN - SCOPUS:35248843253

SN - 3540406999

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 166

EP - 177

BT - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

A2 - Burke, Edmund

A2 - De Causmaecker, Patrick

PB - Springer Verlag

ER -