Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Hopfield neural networks for timetabling: formulations, methods, and comparative results
Computers and Industrial Engineering - Special issue: Focussed issue on applied meta-heuristics
Case-based selection of initialisation heuristics for metaheuristic examination timetabling
Expert Systems with Applications: An International Journal
Activity and value orientated decision support for the development planning of a theme park
Expert Systems with Applications: An International Journal
Proceedings of the 9th annual conference companion on Genetic and evolutionary computation
Some experiments with ant colony algorithms for the exam timetabling problem
ANTS'06 Proceedings of the 5th international conference on Ant Colony Optimization and Swarm Intelligence
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The main purpose of scheduling exhibition projects for art museums is to provide the visitors with more exhibitions and to utilize the galleries as fully as possible. Because the combinations of possible exhibitions for all galleries at any given time are numerous, it is difficult for the art museum's planner to make an optimal decision. Therefore, this paper developed a decision support model with genetic algorithms, called SCHEMA (SCHeduling Exhibitions for Museum of Art). In the model the galleries are the resource which the exhibitions utilize in the sequence of their priority values. The model's evaluation shows to be significantly effective in planning time, percent usage of the gallery, and the number of exhibitions scheduled. Because all the complex computations are done by the model, the decision making process of the scheduling stage is speeded up considerably.