Parallel Evolutionary Multi-Criterion Optimization for Block Layout Problems
نویسندگان
چکیده
In this paper, a parallel evolutionary multi-criteria optimization algorithm: DGA and DRMOGA are applied to block layout problems. The results are compared to the results of SGA and discussed. Because block layout problems are NP hard and can have several types of objectives, these problems are suitable to evolutionary multicriterion optimization algorithms. DRMOGA is a DGA model that can derive good Pareto solutions in continuous optimization problems. However it has not been applied to discrete problems. In the numerical example, the Pareto solutions of the block layout problem with 13 blocks were derived by DGA, DRMOGA and SGA. It was confirmed that it is difficult to derive the solutions with any model, even if the problem has only one objective. It is also found that good parallel efficiency can be derived from both DGA and DRMOGA. The results of Pareto solutions of DGA and DRMOGA are almost the same. However, DRMOGA searched a wider area than that of DGA.
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