Applying the threshold accepting metaheuristic to curriculum based course timetabling: A contribution to the second international timetabling competition ITC 2007
The article presents a study of local search algorithms for timetabling problems, with the particular goal of providing a contribution to competition track 3 of the International Timetabling Competition 2007 (ITC 2007). In this track, a formulation of a curriculum based course timetabling has been p...
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Veröffentlicht in: | Annals of operations research 2012-04, Vol.194 (1), p.189-202 |
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description | The article presents a study of local search algorithms for timetabling problems, with the particular goal of providing a contribution to competition track 3 of the International Timetabling Competition 2007 (ITC 2007). In this track, a formulation of a curriculum based course timetabling has been published, and novel benchmark instances have been presented that allow the comparison of optimization approaches.
Our heuristic local search procedure is based on the principles of Threshold Accepting, overcoming local optima by a deterministic acceptance of inferior solutions throughout the search runs. A stochastic neighborhood is proposed and implemented, randomly removing and reassigning events from the current solution.
The overall concept has been incrementally obtained from a series of experiments, which we describe in each (sub)section of the paper. In conclusions, we successfully derived a potential candidate solution approach for the finals of track 3 of the ITC 2007, held in August 2008 in Montréal, Canada. |
doi_str_mv | 10.1007/s10479-010-0703-4 |
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Our heuristic local search procedure is based on the principles of Threshold Accepting, overcoming local optima by a deterministic acceptance of inferior solutions throughout the search runs. A stochastic neighborhood is proposed and implemented, randomly removing and reassigning events from the current solution.
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Our heuristic local search procedure is based on the principles of Threshold Accepting, overcoming local optima by a deterministic acceptance of inferior solutions throughout the search runs. A stochastic neighborhood is proposed and implemented, randomly removing and reassigning events from the current solution.
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Our heuristic local search procedure is based on the principles of Threshold Accepting, overcoming local optima by a deterministic acceptance of inferior solutions throughout the search runs. A stochastic neighborhood is proposed and implemented, randomly removing and reassigning events from the current solution.
The overall concept has been incrementally obtained from a series of experiments, which we describe in each (sub)section of the paper. In conclusions, we successfully derived a potential candidate solution approach for the finals of track 3 of the ITC 2007, held in August 2008 in Montréal, Canada.</abstract><cop>Boston</cop><pub>Springer US</pub><doi>10.1007/s10479-010-0703-4</doi><tpages>14</tpages></addata></record> |
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subjects | Acceptance Benchmarking Business and Management Combinatorics Competition Heuristic programming Operations research Operations Research/Decision Theory Optimization Scheduling (Management) Searching Stochasticity Theory of Computation Thresholds |
title | Applying the threshold accepting metaheuristic to curriculum based course timetabling: A contribution to the second international timetabling competition ITC 2007 |
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