Syariza Abdul Rahman

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In this paper, we combine graph coloring heuristics, namely largest degree and saturation degree with the concept of a heuristic modifier under the framework of squeaky wheel optimization for solving a set of examination timetabling problems. Both components interact adaptively to determine the best ordering of examinations to be processed at each(More)
In this paper, we investigate an adaptive linear combinations of graph coloring heuristics with a heuristic modifier for solving the examination timetabling problem. We invoke a normalisation strategy for each parameter in order to generalise the specific problem data. Two graph coloring heuristics were used in this study (largest degree and saturation(More)
In this study, we investigate an adaptive decomposition strategy that automatically divides examinations into difficult and easy sets in constructing an examination timetable. The examinations in the difficult set are considered to be hard to place and hence are listed before the ones in the easy set. Moreover, examinations within each set are ordered using(More)
Many successful approaches to examination timetabling consist of multiple stages, in which a constructive approach is used for finding a good initial solution, and then one or more improvement approaches are employed successively to further enhance the quality of the solution obtained during the previous stage. Moreover, there is a growing number of studies(More)
Storage and Sharing of data in cloud can be easily modified by user. To overcome this data modification in cloud signature is provided to each individual who access the data in cloud. Once the data is modified by the user on a block, the user must ensure that the signature is provided on that specific block. When the user gets revoked from accessing the(More)
Many successful approaches to examination timetabling consist of multiple stages, in which a constructive approach is used for finding a good initial solution, and then one or more improvement approaches are employed successively to further enhance the quality of the solution obtained during the previous stage. Moreover, there is a growing number of studies(More)
This paper analyses the workload of the drivers for a waste collection benchmark problem. The problem involves ten data sets with different number of customers to be served and different number of disposal facilities available. A heuristic algorithm, namely Different Initial Customer from a previous study is used to solve the problem by constructing(More)
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