multiprocessortask can be stated as finding a schedule for a general graph to execute on a multiprocessor system. In this paper an efficient harmony search algorithm (HSA) is proposed to solve the hybrid flow shop sc...
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ISBN:
(纸本)9781467366014
multiprocessortask can be stated as finding a schedule for a general graph to execute on a multiprocessor system. In this paper an efficient harmony search algorithm (HSA) is proposed to solve the hybrid flow shop scheduling with multiprocessortaskproblems (HFSMTP). The best values of HFS's control parameters are determined by full factorial design. Computational results are compared with the genetic algorithm related to the HFSMTP at the literature. The result showed that the proposed HSA is effective for solving HFSMTP.
In this paper we propose a solution of a multiprocessor task scheduling problem with use of a new meta-heuristic inspired by a model of natural evolution called Generalized Extremal Optimization (GEO). It is inspired ...
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ISBN:
(纸本)9783540896937
In this paper we propose a solution of a multiprocessor task scheduling problem with use of a new meta-heuristic inspired by a model of natural evolution called Generalized Extremal Optimization (GEO). It is inspired by a simple co-evolutionary model based on a Bak-Sneppen model. One of advantages of the model is a simple implementation of potential optimization problems and only one free parameter to adjust;. The idea of GEO metaheuristic and the way of applying it to the multiprocessorschedulingproblem are presented in the paper. In this problem the tasks of a program graph are allocated into multiprocessor system graph where the program completion time is minimized. The problem is know to be a NP-complete problem. In this paper we show that GEO is to able to solve this problem with better performance than genetic algorithm.
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