![]() Further, a SIMD-based parallelĪlgorithm is proposed that has the potential to speed up convergence on multi-processor To a workable timetable if an optimal one is not located. Presented by the given resources and constraints. Test results based on a subset of real-world, working data indicate thatĬonvergence on a feasible (and optimal/Pareto) solution is possible within the search space The constraints are expressed mathematicallyĪnd a conventional algorithm is designed that evaluates solution fitness based on The approach used to formulate the algorithm. Satisfaction problem (CSP) and a theoretical framework is proposed, which guides The timetable problem is modeled as a constraint ![]() To an optimal solution, given its existence. It further aims at proposing a parallel algorithm that is envisaged to speed up convergence Timetabling real-world school resources to fulfil a given set of constraints and preferences. This research aims at designing a genetic algorithm for Timetabling presents an NP-hard combinatorial optimization problem which requiresĪn efficient search algorithm.
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