Research in the domain of school timetabling has essentially focused on applying various techniques such as integer programming, constraint satisfaction, simulated annealing, tabu search and genetic algorithms to calculate a solution to the problem. Optimization techniques like simulated annealing, tabu search and genetic algorithms generally explore a solution space. Hyper-heuristics, on the o...

Employee Timetabling Problems (ETP) are all around us. One possible approach for solving ETPs is to use constraint processing techniques. Another approach is to model human knowledge which is commonly used for solving such problems into knowledge-based systems for timetabling. It is diicult to represent the complex constraints of timetabling explicitly in constraint networks. On the other hand,...

The dynamics of a moving train are usually described by means motion model based on Newton’s second law. This uses as input track geometry data and characteristics like mass, the parameters that running resistance, maximum tractive effort power, brake rates to be applied. It can reproduce predict accurately if mentioned carefully calibrated. constitutes core element broad variety railway applic...

The growing demand for railway capacity has led to high capacity consumption at times and a delay-sensitive network with insufficient robustness. The fundamental challenge is therefore to decide how to increase the robustness. To do so there is a need for accurate measures that return whether the timetable is robust or not and indicate where improvements should be made. Previously presented mea...

[7] G. Lajos. Complete university modular timetabling using constraint logic programming. A constraint-based approach to high-school timetabling problems: A case study. 14 problem diculty is observed. 6 Conclusions We have proposed a constraint satisfaction model for a local high school timetabling problem. The problem we have studied involves an assignment of eight weekly periods to the sectio...

Urban rail transit (URT) is the backbone transport mode in metropolitan areas to accommodate large travel demands. The high energy consumption of URT becomes a hotspot problem due ever-increasing operation mileages and pressing agendas carbon neutralization. model complexity inconsistency objectives minimizing passenger time operational are main challenges for energy-efficient timetabling netwo...

The timetabling problem is well known to be NP complete combinatorial problem. The problem becomes even more complex when addressed to individual timetables of students. The core of dealing with the problem in this application is a timetable builder based on mixed direct-indirect encoding evolved by a genetic algorithm with a self-adaptation paradigm, where the parameters of the genetic algorit...

This work is focused on the application of evolutionary algorithms to solve very complex real-world problems. For this purpose a Genetic Algorithm is designed to solve the Train Timetabling Problem. Optimizing train timetables on a single line track is known to be NP-hard with respect to the number of conflicts in the schedule. This makes it difficult to obtain good solutions to real life probl...

The Train Timetabling Problem (TTP) consists in finding a train schedule on a railway network that satisfies some operational constraints and maximizes some profit function which counts for the efficiency of the infrastructure usage. In practical cases, however, the maximization of the objective function is not enough and one calls for a robust solution that is capable of absorbing as much as p...

In this paper we present an application of Tabu Search (TS) to the exams timetabling problem. One of the drawback of this meta-heuristic is related with some parameter that can affect the performance of the algorithm and must be tuned. One of such is tabu tenure which is much problem dependent. Our goal is to have a automatic process of managing the memory which is important for practical appli...