1,185 research outputs found
Cyclic transfers in school timetabling
In this paper we propose a neighbourhood structure based on sequential/cyclic moves and a cyclic transfer algorithm for the high school timetabling problem. This method enables execution of complex moves for improving an existing solution, while dealing with the challenge of exploring the neighbourhood efficiently. An improvement graph is used in which certain negative cycles correspond to the neighbours; these cycles are explored using a recursive method. We address the problem of applying large neighbourhood structure methods on problems where the cost function is not exactly the sum of independent cost functions, as it is in the set partitioning problem. For computational experiments we use four real world data sets for high school timetabling in the Netherlands and England.We present results of the cyclic transfer algorithm with different settings on these data sets. The costs decrease by 8â28% if we use the cyclic transfers for local optimization compared to our initial solutions. The quality of the best initial solutions are comparable to the solutions found in practice by timetablers
Cyclic transfers in school timetabling
In this paper we propose a neighbourhood structure based\ud
on sequential/cyclic moves and a Cyclic Transfer algorithm for the high school timetabling problem. This method enables execution of complex moves for improving an existing solution, while dealing with the challenge of exploring the neighbourhood efficiently. An improvement graph is used in which certain negative cycles correspond to the neighbours; these cycles are explored using a recursive method. We address the problem of applying large neighbourhood structure methods on problems where the cost function is not exactly the sum of independent cost functions, as it is in the set partitioning problem. For computational experiments we use four real world datasets for high school timetabling in the Netherlands and England. We present results of the cyclic transfer algorithm with different settings on these datasets. The costs decrease by 8% to 28% if we use the cyclic transfers for local optimization compared to our initial solutions. The quality of the best initial solutions are comparable to the solutions found in practice by timetablers
Satisfiers and dissatisfiers for international vocational education students: A case study using narrative frames
While the satisfaction of international students is frequently surveyed, much of this research is based on a very limited range of closed-item data collection methods, producing findings that partially reflect the researchersâ assumptions in designing the survey items. Recognizing the potential value in using methods that are more open-ended and qualitative analyses, the present study employed narrative frames and follow-up interviews to explore the satisfiers and dissatisfiers for international vocational education students at one institution in New Zealand. Reporting on perceptions of the class, institution, and community, the findings identify the participantsâ top-of-mind (dis)satisfiers and complement the existing literature by identifying seldom-reported themes. Discussion of issues in analyzing narrative frames is also provided
Feature-based tuning of simulated annealing applied to the curriculum-based course timetabling problem
We consider the university course timetabling problem, which is one of the
most studied problems in educational timetabling. In particular, we focus our
attention on the formulation known as the curriculum-based course timetabling
problem, which has been tackled by many researchers and for which there are
many available benchmarks.
The contribution of this paper is twofold. First, we propose an effective and
robust single-stage simulated annealing method for solving the problem.
Secondly, we design and apply an extensive and statistically-principled
methodology for the parameter tuning procedure. The outcome of this analysis is
a methodology for modeling the relationship between search method parameters
and instance features that allows us to set the parameters for unseen instances
on the basis of a simple inspection of the instance itself. Using this
methodology, our algorithm, despite its apparent simplicity, has been able to
achieve high quality results on a set of popular benchmarks.
A final contribution of the paper is a novel set of real-world instances,
which could be used as a benchmark for future comparison
Bin Packing and Related Problems: General Arc-flow Formulation with Graph Compression
We present an exact method, based on an arc-flow formulation with side
constraints, for solving bin packing and cutting stock problems --- including
multi-constraint variants --- by simply representing all the patterns in a very
compact graph. Our method includes a graph compression algorithm that usually
reduces the size of the underlying graph substantially without weakening the
model. As opposed to our method, which provides strong models, conventional
models are usually highly symmetric and provide very weak lower bounds.
Our formulation is equivalent to Gilmore and Gomory's, thus providing a very
strong linear relaxation. However, instead of using column-generation in an
iterative process, the method constructs a graph, where paths from the source
to the target node represent every valid packing pattern.
The same method, without any problem-specific parameterization, was used to
solve a large variety of instances from several different cutting and packing
problems. In this paper, we deal with vector packing, graph coloring, bin
packing, cutting stock, cardinality constrained bin packing, cutting stock with
cutting knife limitation, cutting stock with binary patterns, bin packing with
conflicts, and cutting stock with binary patterns and forbidden pairs. We
report computational results obtained with many benchmark test data sets, all
of them showing a large advantage of this formulation with respect to the
traditional ones
The Application of Late Acceptance Heuristic Method for the Tanzanian High School Timetabling Problem
High School timetabling is the problem of scheduling lessons of different subjects and teachers to timeslots within a week, while satisfying a set of constraints which are classified into hard and soft constraints. This problem is different from university course timetabling problem because of the differences in structures including classroom allocations and grouping of subject combinations. Given the scarce education resources in developing countries, high school timetabling problem plays a very important role in optimizing the use of meager resources and therefore contribute to improvement of quality of education. The problem has attracted attention of many researchers around the world; however, very little has been done in Tanzania. This paper presents a solution algorithm known as Late Acceptance heuristic for the problem and compares results with previous work on Simulated Annealing and Great Deluge Algorithm for three schools in Dar es Salaam Tanzania. It is concluded that Late Acceptance heuristic gives results which are similar to the previous two algorithms but performs better in terms of time saving.
Keywords: Late Acceptance; High School Timetabling; Combinatorial Optimization; Heuristics; NP-Har
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