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Scheduling tasks onto the processors of a parallel system is a crucial part of program parallelization. Due to the NP-hardness of the task scheduling problem, scheduling algorithms are based on heuristics that try to produce good rather than optimal schedules. This paper proposes a Memetic algorithm with Tabu search and Simulated Annealing as local search for solving Task scheduling problem considering...
In this paper, a genetic algorithm and a tabu search are investigated for the maximum satisfiability problem. When the evolutionary algorithm is hybridized with the randomized procedure G-bit [14], better performance is achieved and it even outperforms the well known probabilistic procedure GSAT[25]. On the other hand, when the random noise strategy is introduced in the tabu search, the latter competes...
This paper analyzes the complexity-performance trade-off of several heuristic near-optimum multiuser detection (MuD) approaches applied to the uplink of synchronous single/multiple-input multiple-output multicarrier code division multiple access (S/MIMO MC-CDMA) systems. Genetic algorithm (GA), short term tabu search (STTS) and reactive tabu search (RTS), simulated annealing (SA), particle swarm optimization...
Optimising a train schedule 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 determine optimum solutions to real life problems in reasonable time and raises the need for good heuristic techniques. The heuristics applied and compared in this paper are a local search heuristic with an improved neighbourhood structure, genetic...
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