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Academic institutions are moving toward automated management of the educational process. One aspect of this process is the exam scheduling. The large number of students, classes, professors, and venues renders the manual scheduling process tedious and useless. In this paper, we describe the efforts of the Arab East College for High Education in Saudi Arabia in scheduling exams in the least number...
Examination scheduling is a very important task that has to be done in all academic institutions periodically. Formulating exam schedules manually requires immense time and effort, due to the presence of a large number of conflicting constraints that must be satisfied. In this study, we tackle the examination scheduling problem that is specific to the female section in our college, and particularly...
Computational grids have become attractive and promising platforms for solving large-scale high-performance applications of multi-institutional interest. However, the management of resources and computational tasks is a critical and complex undertaking as these resources and tasks are geographically distributed and a heterogeneous in nature. This paper proposes a novel Rank Based Genetic Scheduler...
The large computing capacity provided by grid systems is beneficial for solving complex problems by using many nodes of the grid at the same time. The usefulness of a grid system largely depends, among other factors, on the efficiency of the system regarding the allocation of jobs to grid resources. This paper proposes an Roulette Wheel Selection Genetic Algorithm using Best Rank Power(PRRWSGA) for...
In this paper we consider efficient and low complexity scheduling algorithms for multiuser multiple-input multiple-output (MIMO) systems. The optimal user scheduling involves an exhaustive search, which becomes very complex for realistic numbers of users and transmit antennas. Among various suboptimal but low complexity algorithms, greedy algorithms with heuristic scheduling metrics have been shown...
In most cases, the number of resources and tasks in grid computing environment is large. Accordingly, the complexity of task scheduling is significantly increased. This results very complex optimization problem. This paper proposes an improved rank-based roulette wheel selection genetic algorithm (IRRWSGA) for scheduling independent tasks in the grid environment. The modified algorithm speeds up convergence...
In this paper, we consider efficient and low complexity scheduling algorithms for multiuser multiple-input multiple-output (MIMO) systems. Due to the dimensionality constraint imposed by linear precoding techniques like block diagonalization (BD), user scheduling is required. Optimal user scheduling involves an exhaustive search, which becomes very complex for realistic numbers of users and transmit...
In grid computing the number of resources and tasks is usually very large, which makes the scheduling task very complex optimization problem. Genetic algorithms (GAs) have been broadly used to solve these NP-complete problems efficiently. On the other hand, the standard genetic algorithm (SGA) is too slow when used in a realistic scheduling due to its time consuming iteration. This paper proposes...
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