Timetabling Problem is a Multi-objective Combination Optimization Problem with constraints, and also has been proved as NP-Completed problem. Genetic Algorithm is a high-effective Paralleling Processing, randomly searching and self-applicable algorithm based on the development of the nature evolution and option, it is a very effective algorithm to resolve NP-Completed Combination Optimization Problem. Genetic Algorithm is
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Timetabling problem is a typical combinatorial optimization and an uncertain scheduling problem. With the development of artificial intelligence technologies, people have had a strong need in automation solution for timetabling problem.Ant colony optimization derived from the field of swarm intelligence. It has a good global search capability, a wide range of applications in optimization problem.This
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The timetabling problem (TP) is an NP-hard multiobjective combinatorial optimization problem with constraints. Therefore, it is much unlikely that there exist a polynomial-time algorithm for the TP.Genetic algorithms (GAs) are a large class of efficient randomly searching algorithms that mimic the evolution of species, which are often employed to approximately solve NP-hard Problems. This thesis
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In order to ensure the quality of tuition, a university must establish a set of normal teaching plans, while arranging courses is an important step of carrying out the teaching plan successfully. With the increasing quantity of college students, the scale of data are huge, and all kinds of constraints are complex, courses arrangement becomes
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Timetabling problem is a constrained, multi-objective combinatorial optimization problem, and has been proved to be a NP complete problem.Genetic algorithm based on the biological mechanism of natural selection and heredity and leveraging colony searching technology, is particularly applicable for the resolution of complicated non-linear problems intractable with traditional searching methods. For nearly 40 years’development, Genetic
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Timetabling problem is a constrained, multi-objective combinatorial optimization problem, and has been proved to be a NP complete problem.Genetic algorithm based on the biological mechanism of natural selection and heredity and leveraging colony searching technology, is particularly applicable for the resolution of complicated non-linear problems intractable with traditional searching methods. For nearly 40 years’development, Genetic
(Read More…)
To ensure the quality of teaching, course scheduling becomes an important part of successful implementation of teaching plans. With the rapid expansion of university scale, course scheduling become more and more complicated under the circumstance of the limited teaching resources. Artificial Arrangement is not only a heavy workload, but also a complexity of cross-linking of
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