开放式创新模拟中的交叉受精与协作

Albrecht Fritzsche
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引用次数: 1

摘要

进化模型允许我们通过计算机模拟遗传算法来接近创新。在这些模型中,可以从不同的角度考虑开放式创新。David Goldberg提出了一个流行的模型,将进化过程中的元素重组与杂交受精活动中的信息交换联系起来。另一种可能性是对具有特定技能和经验的贡献者的协作进行建模,通过复杂的变革操作者系统地改进创新环境的某些方面。对置换流水车间调度问题的仿真表明,在考虑一定约束条件的情况下,使用这些算子确实可以提高求解的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Cross-fertilization vs. Collaboration in Simulations of Open Innovation
Evolutionary models allow us to approach innovation by the means of computer simulation with genetic algorithms. Open innovation can be considered in these models in different ways. A popular model by David Goldberg connects re-combinations of elements during evolutionary processes with the exchange of information in cross-fertilization activities. Another possibility is to model the collaboration of contributors with specific skills and experiences through sophisticated change operators that work systematically on improvements with respect to certain aspects of the innovation context. A simulation of this procedure on an instance of the permutation flow shop scheduling problem shows that the usage of these operators can indeed increase the performance of the solution generation, if certain constraints are kept in consideration.
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